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<title>quapy.classification.calibration — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
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@ -83,9 +84,7 @@
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<span class="c1"># see https://github.com/kundajelab/abstention</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifier">
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifier">[docs]</a>
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<span class="k">class</span> <span class="nc">RecalibratedProbabilisticClassifier</span><span class="p">:</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifier"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifier">[docs]</a><span class="k">class</span> <span class="nc">RecalibratedProbabilisticClassifier</span><span class="p">:</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Abstract class for (re)calibration method from `abstention.calibration`, as defined in</span>
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<span class="sd"> `Alexandari, A., Kundaje, A., & Shrikumar, A. (2020, November). Maximum likelihood with bias-corrected calibration</span>
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@ -95,10 +94,7 @@
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<span class="k">pass</span></div>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase">
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase">[docs]</a>
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<span class="k">class</span> <span class="nc">RecalibratedProbabilisticClassifierBase</span><span class="p">(</span><span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">RecalibratedProbabilisticClassifier</span><span class="p">):</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase">[docs]</a><span class="k">class</span> <span class="nc">RecalibratedProbabilisticClassifierBase</span><span class="p">(</span><span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">RecalibratedProbabilisticClassifier</span><span class="p">):</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Applies a (re)calibration method from `abstention.calibration`, as defined in</span>
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<span class="sd"> `Alexandari et al. paper <http://proceedings.mlr.press/v119/alexandari20a.html>`_.</span>
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@ -121,9 +117,7 @@
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<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">n_jobs</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.fit">
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit">[docs]</a>
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<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.fit"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Fits the calibration for the probabilistic classifier.</span>
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@ -141,10 +135,7 @@
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<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'wrong value for val_split: the proportion of validation documents must be in (0,1)'</span><span class="p">)</span>
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<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">fit_tr_val</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span></div>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.fit_cv">
|
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_cv">[docs]</a>
|
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<span class="k">def</span> <span class="nf">fit_cv</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.fit_cv"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_cv">[docs]</a> <span class="k">def</span> <span class="nf">fit_cv</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Fits the calibration in a cross-validation manner, i.e., it generates posterior probabilities for all</span>
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<span class="sd"> training instances via cross-validation, and then retrains the classifier on all training instances.</span>
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@ -162,10 +153,7 @@
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<span class="bp">self</span><span class="o">.</span><span class="n">calibration_function</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calibrator</span><span class="p">(</span><span class="n">posteriors</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">eye</span><span class="p">(</span><span class="n">nclasses</span><span class="p">)[</span><span class="n">y</span><span class="p">],</span> <span class="n">posterior_supplied</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<span class="k">return</span> <span class="bp">self</span></div>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.fit_tr_val">
|
||||
<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_tr_val">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit_tr_val</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.fit_tr_val"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_tr_val">[docs]</a> <span class="k">def</span> <span class="nf">fit_tr_val</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Fits the calibration in a train/val-split manner, i.e.t, it partitions the training instances into a</span>
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<span class="sd"> training and a validation set, and then uses the training samples to learn classifier which is then used</span>
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@ -183,10 +171,7 @@
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<span class="bp">self</span><span class="o">.</span><span class="n">calibration_function</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calibrator</span><span class="p">(</span><span class="n">posteriors</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">eye</span><span class="p">(</span><span class="n">nclasses</span><span class="p">)[</span><span class="n">yva</span><span class="p">],</span> <span class="n">posterior_supplied</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<span class="k">return</span> <span class="bp">self</span></div>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.predict">
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict">[docs]</a>
|
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<span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.predict"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict">[docs]</a> <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Predicts class labels for the data instances in `X`</span>
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@ -195,10 +180,7 @@
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<span class="sd"> """</span>
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<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X</span><span class="p">)</span></div>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.predict_proba">
|
||||
<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict_proba">[docs]</a>
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<span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
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<div class="viewcode-block" id="RecalibratedProbabilisticClassifierBase.predict_proba"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict_proba">[docs]</a> <span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Generates posterior probabilities for the data instances in `X`</span>
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@ -208,7 +190,6 @@
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<span class="n">posteriors</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">predict_proba</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
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<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">calibration_function</span><span class="p">(</span><span class="n">posteriors</span><span class="p">)</span></div>
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<span class="nd">@property</span>
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<span class="k">def</span> <span class="nf">classes_</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
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<span class="w"> </span><span class="sd">"""</span>
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@ -219,10 +200,7 @@
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<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">classes_</span></div>
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<div class="viewcode-block" id="NBVSCalibration">
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.NBVSCalibration">[docs]</a>
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<span class="k">class</span> <span class="nc">NBVSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
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<div class="viewcode-block" id="NBVSCalibration"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.NBVSCalibration">[docs]</a><span class="k">class</span> <span class="nc">NBVSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
|
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<span class="w"> </span><span class="sd">"""</span>
|
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<span class="sd"> Applies the No-Bias Vector Scaling (NBVS) calibration method from `abstention.calibration`, as defined in</span>
|
||||
<span class="sd"> `Alexandari et al. paper <http://proceedings.mlr.press/v119/alexandari20a.html>`_:</span>
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@ -244,10 +222,7 @@
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<span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span></div>
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<div class="viewcode-block" id="BCTSCalibration">
|
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.BCTSCalibration">[docs]</a>
|
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<span class="k">class</span> <span class="nc">BCTSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
|
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<div class="viewcode-block" id="BCTSCalibration"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.BCTSCalibration">[docs]</a><span class="k">class</span> <span class="nc">BCTSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
|
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<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Applies the Bias-Corrected Temperature Scaling (BCTS) calibration method from `abstention.calibration`, as defined in</span>
|
||||
<span class="sd"> `Alexandari et al. paper <http://proceedings.mlr.press/v119/alexandari20a.html>`_:</span>
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@ -269,10 +244,7 @@
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<span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span></div>
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<div class="viewcode-block" id="TSCalibration">
|
||||
<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.TSCalibration">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">TSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
|
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<div class="viewcode-block" id="TSCalibration"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.TSCalibration">[docs]</a><span class="k">class</span> <span class="nc">TSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
|
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<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Applies the Temperature Scaling (TS) calibration method from `abstention.calibration`, as defined in</span>
|
||||
<span class="sd"> `Alexandari et al. paper <http://proceedings.mlr.press/v119/alexandari20a.html>`_:</span>
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@ -294,10 +266,7 @@
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<span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span></div>
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<div class="viewcode-block" id="VSCalibration">
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<a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.VSCalibration">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">VSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="VSCalibration"><a class="viewcode-back" href="../../../quapy.classification.html#quapy.classification.calibration.VSCalibration">[docs]</a><span class="k">class</span> <span class="nc">VSCalibration</span><span class="p">(</span><span class="n">RecalibratedProbabilisticClassifierBase</span><span class="p">):</span>
|
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<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Applies the Vector Scaling (VS) calibration method from `abstention.calibration`, as defined in</span>
|
||||
<span class="sd"> `Alexandari et al. paper <http://proceedings.mlr.press/v119/alexandari20a.html>`_:</span>
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@ -318,7 +287,6 @@
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<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">n_jobs</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
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<html class="writer-html5" lang="en" data-content_root="../../../">
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<title>quapy.data.datasets — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
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@ -70,11 +71,8 @@
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<div itemprop="articleBody">
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<h1>Source code for quapy.data.datasets</h1><div class="highlight"><pre>
|
||||
<div class="viewcode-block" id="warn">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.warn">[docs]</a>
|
||||
<span></span><span class="k">def</span> <span class="nf">warn</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="warn"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.warn">[docs]</a><span></span><span class="k">def</span> <span class="nf">warn</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">warnings</span>
|
||||
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span> <span class="o">=</span> <span class="n">warn</span>
|
||||
<span class="kn">import</span> <span class="nn">os</span>
|
||||
|
|
@ -142,9 +140,7 @@
|
|||
<span class="p">}</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_reviews">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_reviews">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_reviews</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">tfidf</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">min_df</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">pickle</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="fetch_reviews"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_reviews">[docs]</a><span class="k">def</span> <span class="nf">fetch_reviews</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">tfidf</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">min_df</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">pickle</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads a Reviews dataset as a Dataset instance, as used in</span>
|
||||
<span class="sd"> `Esuli, A., Moreo, A., and Sebastiani, F. "A recurrent neural network for sentiment quantification."</span>
|
||||
|
|
@ -190,10 +186,7 @@
|
|||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_twitter">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_twitter">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_twitter</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">for_model_selection</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">min_df</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">pickle</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="fetch_twitter"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_twitter">[docs]</a><span class="k">def</span> <span class="nf">fetch_twitter</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">for_model_selection</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">min_df</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">pickle</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads a Twitter dataset as a :class:`quapy.data.base.Dataset` instance, as used in:</span>
|
||||
<span class="sd"> `Gao, W., Sebastiani, F.: From classification to quantification in tweet sentiment analysis.</span>
|
||||
|
|
@ -267,10 +260,7 @@
|
|||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_UCIBinaryDataset">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIBinaryDataset">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_UCIBinaryDataset</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">test_split</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="fetch_UCIBinaryDataset"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIBinaryDataset">[docs]</a><span class="k">def</span> <span class="nf">fetch_UCIBinaryDataset</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">test_split</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads a UCI dataset as an instance of :class:`quapy.data.base.Dataset`, as used in</span>
|
||||
<span class="sd"> `Pérez-Gállego, P., Quevedo, J. R., & del Coz, J. J. (2017).</span>
|
||||
|
|
@ -295,10 +285,7 @@
|
|||
<span class="k">return</span> <span class="n">Dataset</span><span class="p">(</span><span class="o">*</span><span class="n">data</span><span class="o">.</span><span class="n">split_stratified</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">test_split</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_UCIBinaryLabelledCollection">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIBinaryLabelledCollection">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_UCIBinaryLabelledCollection</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">LabelledCollection</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="fetch_UCIBinaryLabelledCollection"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIBinaryLabelledCollection">[docs]</a><span class="k">def</span> <span class="nf">fetch_UCIBinaryLabelledCollection</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">LabelledCollection</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads a UCI collection as an instance of :class:`quapy.data.base.LabelledCollection`, as used in</span>
|
||||
<span class="sd"> `Pérez-Gállego, P., Quevedo, J. R., & del Coz, J. J. (2017).</span>
|
||||
|
|
@ -642,10 +629,7 @@
|
|||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_UCIMulticlassDataset">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIMulticlassDataset">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_UCIMulticlassDataset</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">test_split</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="fetch_UCIMulticlassDataset"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIMulticlassDataset">[docs]</a><span class="k">def</span> <span class="nf">fetch_UCIMulticlassDataset</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">test_split</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">Dataset</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads a UCI multiclass dataset as an instance of :class:`quapy.data.base.Dataset`. </span>
|
||||
|
||||
|
|
@ -675,10 +659,7 @@
|
|||
<span class="k">return</span> <span class="n">Dataset</span><span class="p">(</span><span class="o">*</span><span class="n">data</span><span class="o">.</span><span class="n">split_stratified</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">test_split</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_UCIMulticlassLabelledCollection">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIMulticlassLabelledCollection">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_UCIMulticlassLabelledCollection</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">LabelledCollection</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="fetch_UCIMulticlassLabelledCollection"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_UCIMulticlassLabelledCollection">[docs]</a><span class="k">def</span> <span class="nf">fetch_UCIMulticlassLabelledCollection</span><span class="p">(</span><span class="n">dataset_name</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-></span> <span class="n">LabelledCollection</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads a UCI multiclass collection as an instance of :class:`quapy.data.base.LabelledCollection`.</span>
|
||||
|
||||
|
|
@ -751,14 +732,11 @@
|
|||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_df_replace</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">col</span><span class="p">,</span> <span class="n">repl</span><span class="o">=</span><span class="p">{</span><span class="s1">'yes'</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">'no'</span><span class="p">:</span><span class="mi">0</span><span class="p">},</span> <span class="n">astype</span><span class="o">=</span><span class="nb">float</span><span class="p">):</span>
|
||||
<span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="n">repl</span><span class="p">[</span><span class="n">x</span><span class="p">])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">astype</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_lequa2022">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_lequa2022">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_lequa2022</span><span class="p">(</span><span class="n">task</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="fetch_lequa2022"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_lequa2022">[docs]</a><span class="k">def</span> <span class="nf">fetch_lequa2022</span><span class="p">(</span><span class="n">task</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads the official datasets provided for the `LeQua <https://lequa2022.github.io/index>`_ competition.</span>
|
||||
<span class="sd"> In brief, there are 4 tasks (T1A, T1B, T2A, T2B) having to do with text quantification</span>
|
||||
|
|
@ -830,10 +808,7 @@
|
|||
<span class="k">return</span> <span class="n">train</span><span class="p">,</span> <span class="n">val_gen</span><span class="p">,</span> <span class="n">test_gen</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fetch_IFCB">
|
||||
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_IFCB">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fetch_IFCB</span><span class="p">(</span><span class="n">single_sample_train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">for_model_selection</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="fetch_IFCB"><a class="viewcode-back" href="../../../quapy.data.html#quapy.data.datasets.fetch_IFCB">[docs]</a><span class="k">def</span> <span class="nf">fetch_IFCB</span><span class="p">(</span><span class="n">single_sample_train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">for_model_selection</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">data_home</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Loads the IFCB dataset for quantification from `Zenodo <https://zenodo.org/records/10036244>`_ (for more</span>
|
||||
<span class="sd"> information on this dataset, please follow the zenodo link).</span>
|
||||
|
|
@ -912,7 +887,6 @@
|
|||
<span class="k">return</span> <span class="n">train</span><span class="p">,</span> <span class="n">test_gen</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">train_gen</span><span class="p">,</span> <span class="n">test_gen</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
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@ -77,9 +78,7 @@
|
|||
<span class="kn">import</span> <span class="nn">quapy</span> <span class="k">as</span> <span class="nn">qp</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="from_name">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.from_name">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">from_name</span><span class="p">(</span><span class="n">err_name</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="from_name"><a class="viewcode-back" href="../../quapy.html#quapy.error.from_name">[docs]</a><span class="k">def</span> <span class="nf">from_name</span><span class="p">(</span><span class="n">err_name</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Gets an error function from its name. E.g., `from_name("mae")`</span>
|
||||
<span class="sd"> will return function :meth:`quapy.error.mae`</span>
|
||||
|
||||
|
|
@ -91,10 +90,7 @@
|
|||
<span class="k">return</span> <span class="n">callable_error</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="f1e">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.f1e">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">f1e</span><span class="p">(</span><span class="n">y_true</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="f1e"><a class="viewcode-back" href="../../quapy.html#quapy.error.f1e">[docs]</a><span class="k">def</span> <span class="nf">f1e</span><span class="p">(</span><span class="n">y_true</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""F1 error: simply computes the error in terms of macro :math:`F_1`, i.e.,</span>
|
||||
<span class="sd"> :math:`1-F_1^M`, where :math:`F_1` is the harmonic mean of precision and recall,</span>
|
||||
<span class="sd"> defined as :math:`\\frac{2tp}{2tp+fp+fn}`, with `tp`, `fp`, and `fn` standing</span>
|
||||
|
|
@ -109,10 +105,7 @@
|
|||
<span class="k">return</span> <span class="mf">1.</span> <span class="o">-</span> <span class="n">f1_score</span><span class="p">(</span><span class="n">y_true</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">,</span> <span class="n">average</span><span class="o">=</span><span class="s1">'macro'</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="acce">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.acce">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">acce</span><span class="p">(</span><span class="n">y_true</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="acce"><a class="viewcode-back" href="../../quapy.html#quapy.error.acce">[docs]</a><span class="k">def</span> <span class="nf">acce</span><span class="p">(</span><span class="n">y_true</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the error in terms of 1-accuracy. The accuracy is computed as</span>
|
||||
<span class="sd"> :math:`\\frac{tp+tn}{tp+fp+fn+tn}`, with `tp`, `fp`, `fn`, and `tn` standing</span>
|
||||
<span class="sd"> for true positives, false positives, false negatives, and true negatives,</span>
|
||||
|
|
@ -125,10 +118,7 @@
|
|||
<span class="k">return</span> <span class="mf">1.</span> <span class="o">-</span> <span class="p">(</span><span class="n">y_true</span> <span class="o">==</span> <span class="n">y_pred</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.mae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mae"><a class="viewcode-back" href="../../quapy.html#quapy.error.mae">[docs]</a><span class="k">def</span> <span class="nf">mae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the mean absolute error (see :meth:`quapy.error.ae`) across the sample pairs.</span>
|
||||
|
||||
<span class="sd"> :param prevs: array-like of shape `(n_samples, n_classes,)` with the true prevalence values</span>
|
||||
|
|
@ -139,10 +129,7 @@
|
|||
<span class="k">return</span> <span class="n">ae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.ae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">ae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ae"><a class="viewcode-back" href="../../quapy.html#quapy.error.ae">[docs]</a><span class="k">def</span> <span class="nf">ae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the absolute error between the two prevalence vectors.</span>
|
||||
<span class="sd"> Absolute error between two prevalence vectors :math:`p` and :math:`\\hat{p}` is computed as</span>
|
||||
<span class="sd"> :math:`AE(p,\\hat{p})=\\frac{1}{|\\mathcal{Y}|}\\sum_{y\\in \\mathcal{Y}}|\\hat{p}(y)-p(y)|`,</span>
|
||||
|
|
@ -156,10 +143,7 @@
|
|||
<span class="k">return</span> <span class="nb">abs</span><span class="p">(</span><span class="n">prevs_hat</span> <span class="o">-</span> <span class="n">prevs</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="nae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.nae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">nae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="nae"><a class="viewcode-back" href="../../quapy.html#quapy.error.nae">[docs]</a><span class="k">def</span> <span class="nf">nae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the normalized absolute error between the two prevalence vectors.</span>
|
||||
<span class="sd"> Normalized absolute error between two prevalence vectors :math:`p` and :math:`\\hat{p}` is computed as</span>
|
||||
<span class="sd"> :math:`NAE(p,\\hat{p})=\\frac{AE(p,\\hat{p})}{z_{AE}}`,</span>
|
||||
|
|
@ -174,10 +158,7 @@
|
|||
<span class="k">return</span> <span class="nb">abs</span><span class="p">(</span><span class="n">prevs_hat</span> <span class="o">-</span> <span class="n">prevs</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="p">(</span><span class="mi">1</span><span class="o">-</span><span class="n">prevs</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mnae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.mnae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mnae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mnae"><a class="viewcode-back" href="../../quapy.html#quapy.error.mnae">[docs]</a><span class="k">def</span> <span class="nf">mnae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the mean normalized absolute error (see :meth:`quapy.error.nae`) across the sample pairs.</span>
|
||||
|
||||
<span class="sd"> :param prevs: array-like of shape `(n_samples, n_classes,)` with the true prevalence values</span>
|
||||
|
|
@ -188,10 +169,7 @@
|
|||
<span class="k">return</span> <span class="n">nae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mse">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.mse">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mse</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mse"><a class="viewcode-back" href="../../quapy.html#quapy.error.mse">[docs]</a><span class="k">def</span> <span class="nf">mse</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the mean squared error (see :meth:`quapy.error.se`) across the sample pairs.</span>
|
||||
|
||||
<span class="sd"> :param prevs: array-like of shape `(n_samples, n_classes,)` with the</span>
|
||||
|
|
@ -203,10 +181,7 @@
|
|||
<span class="k">return</span> <span class="n">se</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="se">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.se">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">se</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="se"><a class="viewcode-back" href="../../quapy.html#quapy.error.se">[docs]</a><span class="k">def</span> <span class="nf">se</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the squared error between the two prevalence vectors.</span>
|
||||
<span class="sd"> Squared error between two prevalence vectors :math:`p` and :math:`\\hat{p}` is computed as</span>
|
||||
<span class="sd"> :math:`SE(p,\\hat{p})=\\frac{1}{|\\mathcal{Y}|}\\sum_{y\\in \\mathcal{Y}}(\\hat{p}(y)-p(y))^2`,</span>
|
||||
|
|
@ -220,10 +195,7 @@
|
|||
<span class="k">return</span> <span class="p">((</span><span class="n">prevs_hat</span> <span class="o">-</span> <span class="n">prevs</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mkld">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.mkld">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mkld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mkld"><a class="viewcode-back" href="../../quapy.html#quapy.error.mkld">[docs]</a><span class="k">def</span> <span class="nf">mkld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the mean Kullback-Leibler divergence (see :meth:`quapy.error.kld`) across the</span>
|
||||
<span class="sd"> sample pairs. The distributions are smoothed using the `eps` factor</span>
|
||||
<span class="sd"> (see :meth:`quapy.error.smooth`).</span>
|
||||
|
|
@ -241,10 +213,7 @@
|
|||
<span class="k">return</span> <span class="n">kld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="kld">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.kld">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">kld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="kld"><a class="viewcode-back" href="../../quapy.html#quapy.error.kld">[docs]</a><span class="k">def</span> <span class="nf">kld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the Kullback-Leibler divergence between the two prevalence distributions.</span>
|
||||
<span class="sd"> Kullback-Leibler divergence between two prevalence distributions :math:`p` and :math:`\\hat{p}`</span>
|
||||
<span class="sd"> is computed as</span>
|
||||
|
|
@ -267,10 +236,7 @@
|
|||
<span class="k">return</span> <span class="p">(</span><span class="n">smooth_prevs</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">smooth_prevs</span><span class="o">/</span><span class="n">smooth_prevs_hat</span><span class="p">))</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mnkld">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.mnkld">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mnkld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mnkld"><a class="viewcode-back" href="../../quapy.html#quapy.error.mnkld">[docs]</a><span class="k">def</span> <span class="nf">mnkld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the mean Normalized Kullback-Leibler divergence (see :meth:`quapy.error.nkld`)</span>
|
||||
<span class="sd"> across the sample pairs. The distributions are smoothed using the `eps` factor</span>
|
||||
<span class="sd"> (see :meth:`quapy.error.smooth`).</span>
|
||||
|
|
@ -287,10 +253,7 @@
|
|||
<span class="k">return</span> <span class="n">nkld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="nkld">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.nkld">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">nkld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="nkld"><a class="viewcode-back" href="../../quapy.html#quapy.error.nkld">[docs]</a><span class="k">def</span> <span class="nf">nkld</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the Normalized Kullback-Leibler divergence between the two prevalence distributions.</span>
|
||||
<span class="sd"> Normalized Kullback-Leibler divergence between two prevalence distributions :math:`p` and</span>
|
||||
<span class="sd"> :math:`\\hat{p}` is computed as</span>
|
||||
|
|
@ -311,10 +274,7 @@
|
|||
<span class="k">return</span> <span class="mf">2.</span> <span class="o">*</span> <span class="n">ekld</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">ekld</span><span class="p">)</span> <span class="o">-</span> <span class="mf">1.</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mrae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.mrae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mrae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mrae"><a class="viewcode-back" href="../../quapy.html#quapy.error.mrae">[docs]</a><span class="k">def</span> <span class="nf">mrae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the mean relative absolute error (see :meth:`quapy.error.rae`) across</span>
|
||||
<span class="sd"> the sample pairs. The distributions are smoothed using the `eps` factor (see</span>
|
||||
<span class="sd"> :meth:`quapy.error.smooth`).</span>
|
||||
|
|
@ -332,10 +292,7 @@
|
|||
<span class="k">return</span> <span class="n">rae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="rae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.rae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">rae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="rae"><a class="viewcode-back" href="../../quapy.html#quapy.error.rae">[docs]</a><span class="k">def</span> <span class="nf">rae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the absolute relative error between the two prevalence vectors.</span>
|
||||
<span class="sd"> Relative absolute error between two prevalence vectors :math:`p` and :math:`\\hat{p}`</span>
|
||||
<span class="sd"> is computed as</span>
|
||||
|
|
@ -358,10 +315,7 @@
|
|||
<span class="k">return</span> <span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">prevs</span> <span class="o">-</span> <span class="n">prevs_hat</span><span class="p">)</span> <span class="o">/</span> <span class="n">prevs</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="nrae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.nrae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">nrae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="nrae"><a class="viewcode-back" href="../../quapy.html#quapy.error.nrae">[docs]</a><span class="k">def</span> <span class="nf">nrae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the normalized absolute relative error between the two prevalence vectors.</span>
|
||||
<span class="sd"> Relative absolute error between two prevalence vectors :math:`p` and :math:`\\hat{p}`</span>
|
||||
<span class="sd"> is computed as</span>
|
||||
|
|
@ -386,10 +340,7 @@
|
|||
<span class="k">return</span> <span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">prevs</span> <span class="o">-</span> <span class="n">prevs_hat</span><span class="p">)</span> <span class="o">/</span> <span class="n">prevs</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">prevs</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">-</span><span class="mi">1</span><span class="o">+</span><span class="p">(</span><span class="mi">1</span><span class="o">-</span><span class="n">min_p</span><span class="p">)</span><span class="o">/</span><span class="n">min_p</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mnrae">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.mnrae">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mnrae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mnrae"><a class="viewcode-back" href="../../quapy.html#quapy.error.mnrae">[docs]</a><span class="k">def</span> <span class="nf">mnrae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Computes the mean normalized relative absolute error (see :meth:`quapy.error.nrae`) across</span>
|
||||
<span class="sd"> the sample pairs. The distributions are smoothed using the `eps` factor (see</span>
|
||||
<span class="sd"> :meth:`quapy.error.smooth`).</span>
|
||||
|
|
@ -407,10 +358,7 @@
|
|||
<span class="k">return</span> <span class="n">nrae</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">prevs_hat</span><span class="p">,</span> <span class="n">eps</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="smooth">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.error.smooth">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">smooth</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">eps</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="smooth"><a class="viewcode-back" href="../../quapy.html#quapy.error.smooth">[docs]</a><span class="k">def</span> <span class="nf">smooth</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="n">eps</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">""" Smooths a prevalence distribution with :math:`\\epsilon` (`eps`) as:</span>
|
||||
<span class="sd"> :math:`\\underline{p}(y)=\\frac{\\epsilon+p(y)}{\\epsilon|\\mathcal{Y}|+</span>
|
||||
<span class="sd"> \\displaystyle\\sum_{y\\in \\mathcal{Y}}p(y)}`</span>
|
||||
|
|
@ -423,7 +371,6 @@
|
|||
<span class="k">return</span> <span class="p">(</span><span class="n">prevs</span> <span class="o">+</span> <span class="n">eps</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">eps</span> <span class="o">*</span> <span class="n">n_classes</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__check_eps</span><span class="p">(</span><span class="n">eps</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">eps</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">sample_size</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">'SAMPLE_SIZE'</span><span class="p">]</span>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.evaluation — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css" />
|
||||
|
||||
|
||||
<!--[if lt IE 9]>
|
||||
<script src="../../_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
||||
|
||||
<script src="../../_static/jquery.js?v=5d32c60e"></script>
|
||||
<script src="../../_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
||||
<script src="../../_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="../../_static/doctools.js?v=9a2dae69"></script>
|
||||
<script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
|
||||
<script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
|
||||
<script src="../../_static/jquery.js"></script>
|
||||
<script src="../../_static/underscore.js"></script>
|
||||
<script src="../../_static/_sphinx_javascript_frameworks_compat.js"></script>
|
||||
<script src="../../_static/doctools.js"></script>
|
||||
<script src="../../_static/sphinx_highlight.js"></script>
|
||||
<script src="../../_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../search.html" />
|
||||
|
|
@ -79,9 +80,7 @@
|
|||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="prediction">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.evaluation.prediction">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">prediction</span><span class="p">(</span>
|
||||
<div class="viewcode-block" id="prediction"><a class="viewcode-back" href="../../quapy.html#quapy.evaluation.prediction">[docs]</a><span class="k">def</span> <span class="nf">prediction</span><span class="p">(</span>
|
||||
<span class="n">model</span><span class="p">:</span> <span class="n">BaseQuantifier</span><span class="p">,</span>
|
||||
<span class="n">protocol</span><span class="p">:</span> <span class="n">AbstractProtocol</span><span class="p">,</span>
|
||||
<span class="n">aggr_speedup</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'auto'</span><span class="p">,</span>
|
||||
|
|
@ -140,7 +139,6 @@
|
|||
<span class="k">return</span> <span class="n">__prediction_helper</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">quantify</span><span class="p">,</span> <span class="n">protocol</span><span class="p">,</span> <span class="n">verbose</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__prediction_helper</span><span class="p">(</span><span class="n">quantification_fn</span><span class="p">,</span> <span class="n">protocol</span><span class="p">:</span> <span class="n">AbstractProtocol</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<span class="n">true_prevs</span><span class="p">,</span> <span class="n">estim_prevs</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">sample_instances</span><span class="p">,</span> <span class="n">sample_prev</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">protocol</span><span class="p">(),</span> <span class="n">total</span><span class="o">=</span><span class="n">protocol</span><span class="o">.</span><span class="n">total</span><span class="p">(),</span> <span class="n">desc</span><span class="o">=</span><span class="s1">'predicting'</span><span class="p">)</span> <span class="k">if</span> <span class="n">verbose</span> <span class="k">else</span> <span class="n">protocol</span><span class="p">():</span>
|
||||
|
|
@ -153,9 +151,7 @@
|
|||
<span class="k">return</span> <span class="n">true_prevs</span><span class="p">,</span> <span class="n">estim_prevs</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="evaluation_report">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.evaluation.evaluation_report">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">evaluation_report</span><span class="p">(</span><span class="n">model</span><span class="p">:</span> <span class="n">BaseQuantifier</span><span class="p">,</span>
|
||||
<div class="viewcode-block" id="evaluation_report"><a class="viewcode-back" href="../../quapy.html#quapy.evaluation.evaluation_report">[docs]</a><span class="k">def</span> <span class="nf">evaluation_report</span><span class="p">(</span><span class="n">model</span><span class="p">:</span> <span class="n">BaseQuantifier</span><span class="p">,</span>
|
||||
<span class="n">protocol</span><span class="p">:</span> <span class="n">AbstractProtocol</span><span class="p">,</span>
|
||||
<span class="n">error_metrics</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span><span class="n">Callable</span><span class="p">]]</span> <span class="o">=</span> <span class="s1">'mae'</span><span class="p">,</span>
|
||||
<span class="n">aggr_speedup</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'auto'</span><span class="p">,</span>
|
||||
|
|
@ -186,7 +182,6 @@
|
|||
<span class="k">return</span> <span class="n">_prevalence_report</span><span class="p">(</span><span class="n">true_prevs</span><span class="p">,</span> <span class="n">estim_prevs</span><span class="p">,</span> <span class="n">error_metrics</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_prevalence_report</span><span class="p">(</span><span class="n">true_prevs</span><span class="p">,</span> <span class="n">estim_prevs</span><span class="p">,</span> <span class="n">error_metrics</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Callable</span><span class="p">]]</span> <span class="o">=</span> <span class="s1">'mae'</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">error_metrics</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
|
||||
|
|
@ -208,9 +203,7 @@
|
|||
<span class="k">return</span> <span class="n">df</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="evaluate">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.evaluation.evaluate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">evaluate</span><span class="p">(</span>
|
||||
<div class="viewcode-block" id="evaluate"><a class="viewcode-back" href="../../quapy.html#quapy.evaluation.evaluate">[docs]</a><span class="k">def</span> <span class="nf">evaluate</span><span class="p">(</span>
|
||||
<span class="n">model</span><span class="p">:</span> <span class="n">BaseQuantifier</span><span class="p">,</span>
|
||||
<span class="n">protocol</span><span class="p">:</span> <span class="n">AbstractProtocol</span><span class="p">,</span>
|
||||
<span class="n">error_metric</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Callable</span><span class="p">],</span>
|
||||
|
|
@ -242,10 +235,7 @@
|
|||
<span class="k">return</span> <span class="n">error_metric</span><span class="p">(</span><span class="n">true_prevs</span><span class="p">,</span> <span class="n">estim_prevs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="evaluate_on_samples">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.evaluation.evaluate_on_samples">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">evaluate_on_samples</span><span class="p">(</span>
|
||||
<div class="viewcode-block" id="evaluate_on_samples"><a class="viewcode-back" href="../../quapy.html#quapy.evaluation.evaluate_on_samples">[docs]</a><span class="k">def</span> <span class="nf">evaluate_on_samples</span><span class="p">(</span>
|
||||
<span class="n">model</span><span class="p">:</span> <span class="n">BaseQuantifier</span><span class="p">,</span>
|
||||
<span class="n">samples</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">qp</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">LabelledCollection</span><span class="p">],</span>
|
||||
<span class="n">error_metric</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Callable</span><span class="p">],</span>
|
||||
|
|
@ -269,7 +259,6 @@
|
|||
|
||||
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
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<title>quapy.functional — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
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@ -78,9 +79,7 @@
|
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<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
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|
||||
|
||||
<div class="viewcode-block" id="prevalence_linspace">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.prevalence_linspace">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">prevalence_linspace</span><span class="p">(</span><span class="n">n_prevalences</span><span class="o">=</span><span class="mi">21</span><span class="p">,</span> <span class="n">repeats</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">smooth_limits_epsilon</span><span class="o">=</span><span class="mf">0.01</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="prevalence_linspace"><a class="viewcode-back" href="../../quapy.html#quapy.functional.prevalence_linspace">[docs]</a><span class="k">def</span> <span class="nf">prevalence_linspace</span><span class="p">(</span><span class="n">n_prevalences</span><span class="o">=</span><span class="mi">21</span><span class="p">,</span> <span class="n">repeats</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">smooth_limits_epsilon</span><span class="o">=</span><span class="mf">0.01</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Produces an array of uniformly separated values of prevalence.</span>
|
||||
<span class="sd"> By default, produces an array of 21 prevalence values, with</span>
|
||||
|
|
@ -102,10 +101,7 @@
|
|||
<span class="k">return</span> <span class="n">p</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="prevalence_from_labels">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.prevalence_from_labels">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">prevalence_from_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">classes</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="prevalence_from_labels"><a class="viewcode-back" href="../../quapy.html#quapy.functional.prevalence_from_labels">[docs]</a><span class="k">def</span> <span class="nf">prevalence_from_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">classes</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Computed the prevalence values from a vector of labels.</span>
|
||||
|
||||
|
|
@ -123,10 +119,7 @@
|
|||
<span class="k">return</span> <span class="n">prevalences</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="prevalence_from_probabilities">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.prevalence_from_probabilities">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">prevalence_from_probabilities</span><span class="p">(</span><span class="n">posteriors</span><span class="p">,</span> <span class="n">binarize</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="prevalence_from_probabilities"><a class="viewcode-back" href="../../quapy.html#quapy.functional.prevalence_from_probabilities">[docs]</a><span class="k">def</span> <span class="nf">prevalence_from_probabilities</span><span class="p">(</span><span class="n">posteriors</span><span class="p">,</span> <span class="n">binarize</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns a vector of prevalence values from a matrix of posterior probabilities.</span>
|
||||
|
||||
|
|
@ -146,10 +139,7 @@
|
|||
<span class="k">return</span> <span class="n">prevalences</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="as_binary_prevalence">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.as_binary_prevalence">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">as_binary_prevalence</span><span class="p">(</span><span class="n">positive_prevalence</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span> <span class="n">clip_if_necessary</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="as_binary_prevalence"><a class="viewcode-back" href="../../quapy.html#quapy.functional.as_binary_prevalence">[docs]</a><span class="k">def</span> <span class="nf">as_binary_prevalence</span><span class="p">(</span><span class="n">positive_prevalence</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span> <span class="n">clip_if_necessary</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Helper that, given a float representing the prevalence for the positive class, returns a np.ndarray of two</span>
|
||||
<span class="sd"> values representing a binary distribution.</span>
|
||||
|
|
@ -167,10 +157,7 @@
|
|||
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HellingerDistance">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.HellingerDistance">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">HellingerDistance</span><span class="p">(</span><span class="n">P</span><span class="p">,</span> <span class="n">Q</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="HellingerDistance"><a class="viewcode-back" href="../../quapy.html#quapy.functional.HellingerDistance">[docs]</a><span class="k">def</span> <span class="nf">HellingerDistance</span><span class="p">(</span><span class="n">P</span><span class="p">,</span> <span class="n">Q</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Computes the Hellingher Distance (HD) between (discretized) distributions `P` and `Q`.</span>
|
||||
<span class="sd"> The HD for two discrete distributions of `k` bins is defined as:</span>
|
||||
|
|
@ -185,10 +172,7 @@
|
|||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">P</span><span class="p">)</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">Q</span><span class="p">))</span><span class="o">**</span><span class="mi">2</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="TopsoeDistance">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.TopsoeDistance">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">TopsoeDistance</span><span class="p">(</span><span class="n">P</span><span class="p">,</span> <span class="n">Q</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="mf">1e-20</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="TopsoeDistance"><a class="viewcode-back" href="../../quapy.html#quapy.functional.TopsoeDistance">[docs]</a><span class="k">def</span> <span class="nf">TopsoeDistance</span><span class="p">(</span><span class="n">P</span><span class="p">,</span> <span class="n">Q</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="mf">1e-20</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Topsoe distance between two (discretized) distributions `P` and `Q`.</span>
|
||||
<span class="sd"> The Topsoe distance for two discrete distributions of `k` bins is defined as:</span>
|
||||
|
|
@ -202,12 +186,9 @@
|
|||
<span class="sd"> :return: float</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">P</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">((</span><span class="mi">2</span><span class="o">*</span><span class="n">P</span><span class="o">+</span><span class="n">epsilon</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">P</span><span class="o">+</span><span class="n">Q</span><span class="o">+</span><span class="n">epsilon</span><span class="p">))</span> <span class="o">+</span> <span class="n">Q</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">((</span><span class="mi">2</span><span class="o">*</span><span class="n">Q</span><span class="o">+</span><span class="n">epsilon</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="n">P</span><span class="o">+</span><span class="n">Q</span><span class="o">+</span><span class="n">epsilon</span><span class="p">)))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="uniform_prevalence_sampling">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.uniform_prevalence_sampling">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">uniform_prevalence_sampling</span><span class="p">(</span><span class="n">n_classes</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="uniform_prevalence_sampling"><a class="viewcode-back" href="../../quapy.html#quapy.functional.uniform_prevalence_sampling">[docs]</a><span class="k">def</span> <span class="nf">uniform_prevalence_sampling</span><span class="p">(</span><span class="n">n_classes</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements the `Kraemer algorithm <http://www.cs.cmu.edu/~nasmith/papers/smith+tromble.tr04.pdf>`_</span>
|
||||
<span class="sd"> for sampling uniformly at random from the unit simplex. This implementation is adapted from this</span>
|
||||
|
|
@ -233,13 +214,10 @@
|
|||
<span class="k">return</span> <span class="n">u</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="n">uniform_simplex_sampling</span> <span class="o">=</span> <span class="n">uniform_prevalence_sampling</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="strprev">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.strprev">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">strprev</span><span class="p">(</span><span class="n">prevalences</span><span class="p">,</span> <span class="n">prec</span><span class="o">=</span><span class="mi">3</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="strprev"><a class="viewcode-back" href="../../quapy.html#quapy.functional.strprev">[docs]</a><span class="k">def</span> <span class="nf">strprev</span><span class="p">(</span><span class="n">prevalences</span><span class="p">,</span> <span class="n">prec</span><span class="o">=</span><span class="mi">3</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns a string representation for a prevalence vector. E.g.,</span>
|
||||
|
||||
|
|
@ -253,10 +231,7 @@
|
|||
<span class="k">return</span> <span class="s1">'['</span><span class="o">+</span> <span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">p</span><span class="si">:</span><span class="s1">.</span><span class="si">{</span><span class="n">prec</span><span class="si">}</span><span class="s1">f</span><span class="si">}</span><span class="s1">'</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">prevalences</span><span class="p">])</span> <span class="o">+</span> <span class="s1">']'</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="adjusted_quantification">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.adjusted_quantification">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">adjusted_quantification</span><span class="p">(</span><span class="n">prevalence_estim</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">,</span> <span class="n">clip</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="adjusted_quantification"><a class="viewcode-back" href="../../quapy.html#quapy.functional.adjusted_quantification">[docs]</a><span class="k">def</span> <span class="nf">adjusted_quantification</span><span class="p">(</span><span class="n">prevalence_estim</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">,</span> <span class="n">clip</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements the adjustment of ACC and PACC for the binary case. The adjustment for a prevalence estimate of the</span>
|
||||
<span class="sd"> positive class `p` comes down to computing:</span>
|
||||
|
|
@ -280,10 +255,7 @@
|
|||
<span class="k">return</span> <span class="n">adjusted</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="normalize_prevalence">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.normalize_prevalence">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">normalize_prevalence</span><span class="p">(</span><span class="n">prevalences</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="normalize_prevalence"><a class="viewcode-back" href="../../quapy.html#quapy.functional.normalize_prevalence">[docs]</a><span class="k">def</span> <span class="nf">normalize_prevalence</span><span class="p">(</span><span class="n">prevalences</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Normalize a vector or matrix of prevalence values. The normalization consists of applying a L1 normalization in</span>
|
||||
<span class="sd"> cases in which the prevalence values are not all-zeros, and to convert the prevalence values into `1/n_classes` in</span>
|
||||
|
|
@ -305,7 +277,6 @@
|
|||
<span class="k">return</span> <span class="n">prevalences</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__num_prevalence_combinations_depr</span><span class="p">(</span><span class="n">n_prevpoints</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_repeats</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Computes the number of prevalence combinations in the n_classes-dimensional simplex if `nprevpoints` equally distant</span>
|
||||
|
|
@ -330,9 +301,7 @@
|
|||
<span class="k">return</span> <span class="n">__f</span><span class="p">(</span><span class="n">n_classes</span><span class="p">,</span> <span class="n">n_prevpoints</span><span class="p">)</span> <span class="o">*</span> <span class="n">n_repeats</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="num_prevalence_combinations">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.num_prevalence_combinations">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">num_prevalence_combinations</span><span class="p">(</span><span class="n">n_prevpoints</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_repeats</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="num_prevalence_combinations"><a class="viewcode-back" href="../../quapy.html#quapy.functional.num_prevalence_combinations">[docs]</a><span class="k">def</span> <span class="nf">num_prevalence_combinations</span><span class="p">(</span><span class="n">n_prevpoints</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_repeats</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Computes the number of valid prevalence combinations in the n_classes-dimensional simplex if `n_prevpoints` equally</span>
|
||||
<span class="sd"> distant prevalence values are generated and `n_repeats` repetitions are requested.</span>
|
||||
|
|
@ -357,10 +326,7 @@
|
|||
<span class="k">return</span> <span class="nb">int</span><span class="p">(</span><span class="n">scipy</span><span class="o">.</span><span class="n">special</span><span class="o">.</span><span class="n">binom</span><span class="p">(</span><span class="n">N</span> <span class="o">+</span> <span class="n">C</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="n">C</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">r</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_nprevpoints_approximation">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.get_nprevpoints_approximation">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_nprevpoints_approximation</span><span class="p">(</span><span class="n">combinations_budget</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_repeats</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="get_nprevpoints_approximation"><a class="viewcode-back" href="../../quapy.html#quapy.functional.get_nprevpoints_approximation">[docs]</a><span class="k">def</span> <span class="nf">get_nprevpoints_approximation</span><span class="p">(</span><span class="n">combinations_budget</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">n_repeats</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Searches for the largest number of (equidistant) prevalence points to define for each of the `n_classes` classes so</span>
|
||||
<span class="sd"> that the number of valid prevalence values generated as combinations of prevalence points (points in a</span>
|
||||
|
|
@ -381,10 +347,7 @@
|
|||
<span class="n">n_prevpoints</span> <span class="o">+=</span> <span class="mi">1</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="check_prevalence_vector">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.check_prevalence_vector">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">check_prevalence_vector</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">raise_exception</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">toleranze</span><span class="o">=</span><span class="mf">1e-08</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="check_prevalence_vector"><a class="viewcode-back" href="../../quapy.html#quapy.functional.check_prevalence_vector">[docs]</a><span class="k">def</span> <span class="nf">check_prevalence_vector</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">raise_exception</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">toleranze</span><span class="o">=</span><span class="mf">1e-08</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Checks that p is a valid prevalence vector, i.e., that it contains values in [0,1] and that the values sum up to 1.</span>
|
||||
|
||||
|
|
@ -407,10 +370,7 @@
|
|||
<span class="k">return</span> <span class="kc">True</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_divergence">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.get_divergence">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_divergence</span><span class="p">(</span><span class="n">divergence</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Callable</span><span class="p">]):</span>
|
||||
<div class="viewcode-block" id="get_divergence"><a class="viewcode-back" href="../../quapy.html#quapy.functional.get_divergence">[docs]</a><span class="k">def</span> <span class="nf">get_divergence</span><span class="p">(</span><span class="n">divergence</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Callable</span><span class="p">]):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">divergence</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">divergence</span><span class="o">==</span><span class="s1">'HD'</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">HellingerDistance</span>
|
||||
|
|
@ -424,10 +384,7 @@
|
|||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'argument "divergence" not understood; use a str or a callable function'</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="argmin_prevalence">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.argmin_prevalence">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">argmin_prevalence</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'optim_minimize'</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="argmin_prevalence"><a class="viewcode-back" href="../../quapy.html#quapy.functional.argmin_prevalence">[docs]</a><span class="k">def</span> <span class="nf">argmin_prevalence</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'optim_minimize'</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'optim_minimize'</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">optim_minimize</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'linear_search'</span><span class="p">:</span>
|
||||
|
|
@ -438,10 +395,7 @@
|
|||
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="optim_minimize">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.optim_minimize">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">optim_minimize</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="optim_minimize"><a class="viewcode-back" href="../../quapy.html#quapy.functional.optim_minimize">[docs]</a><span class="k">def</span> <span class="nf">optim_minimize</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Searches for the optimal prevalence values, i.e., an `n_classes`-dimensional vector of the (`n_classes`-1)-simplex</span>
|
||||
<span class="sd"> that yields the smallest lost. This optimization is carried out by means of a constrained search using scipy's</span>
|
||||
|
|
@ -463,10 +417,7 @@
|
|||
<span class="k">return</span> <span class="n">r</span><span class="o">.</span><span class="n">x</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="linear_search">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.functional.linear_search">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">linear_search</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="linear_search"><a class="viewcode-back" href="../../quapy.html#quapy.functional.linear_search">[docs]</a><span class="k">def</span> <span class="nf">linear_search</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Performs a linear search for the best prevalence value in binary problems. The search is carried out by exploring</span>
|
||||
<span class="sd"> the range [0,1] stepping by 0.01. This search is inefficient, and is added only for completeness (some of the</span>
|
||||
|
|
@ -485,7 +436,6 @@
|
|||
<span class="n">prev_selected</span><span class="p">,</span> <span class="n">min_score</span> <span class="o">=</span> <span class="n">prev</span><span class="p">,</span> <span class="n">score</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">([</span><span class="mi">1</span> <span class="o">-</span> <span class="n">prev_selected</span><span class="p">,</span> <span class="n">prev_selected</span><span class="p">])</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.method._kdey — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css?v=92fd9be5" />
|
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<link rel="stylesheet" type="text/css" href="../../../_static/css/theme.css?v=19f00094" />
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<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
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|
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<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
|
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<script src="../../../_static/jquery.js"></script>
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|
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<script src="../../../_static/_sphinx_javascript_frameworks_compat.js"></script>
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<script src="../../../_static/doctools.js"></script>
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<script src="../../../_static/sphinx_highlight.js"></script>
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<script src="../../../_static/js/theme.js"></script>
|
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<link rel="index" title="Index" href="../../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
|
@ -83,9 +84,7 @@
|
|||
<span class="kn">from</span> <span class="nn">sklearn.metrics.pairwise</span> <span class="kn">import</span> <span class="n">rbf_kernel</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEBase">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">KDEBase</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="KDEBase"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase">[docs]</a><span class="k">class</span> <span class="nc">KDEBase</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Common ancestor for KDE-based methods. Implements some common routines.</span>
|
||||
<span class="sd"> """</span>
|
||||
|
|
@ -105,9 +104,7 @@
|
|||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">bandwidth</span><span class="p">,</span> <span class="nb">float</span><span class="p">):</span>
|
||||
<span class="k">assert</span> <span class="mi">0</span> <span class="o"><</span> <span class="n">bandwidth</span> <span class="o"><</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">"the bandwith for KDEy should be in (0,1), since this method models the unit simplex"</span>
|
||||
|
||||
<div class="viewcode-block" id="KDEBase.get_kde_function">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase.get_kde_function">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_kde_function</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">bandwidth</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEBase.get_kde_function"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase.get_kde_function">[docs]</a> <span class="k">def</span> <span class="nf">get_kde_function</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">bandwidth</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Wraps the KDE function from scikit-learn.</span>
|
||||
|
||||
|
|
@ -117,10 +114,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">KernelDensity</span><span class="p">(</span><span class="n">bandwidth</span><span class="o">=</span><span class="n">bandwidth</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEBase.pdf">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase.pdf">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">pdf</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kde</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEBase.pdf"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase.pdf">[docs]</a> <span class="k">def</span> <span class="nf">pdf</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kde</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Wraps the density evalution of scikit-learn's KDE. Scikit-learn returns log-scores (s), so this</span>
|
||||
<span class="sd"> function returns :math:`e^{s}`</span>
|
||||
|
|
@ -131,10 +125,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">kde</span><span class="o">.</span><span class="n">score_samples</span><span class="p">(</span><span class="n">X</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEBase.get_mixture_components">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase.get_mixture_components">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_mixture_components</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">bandwidth</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEBase.get_mixture_components"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEBase.get_mixture_components">[docs]</a> <span class="k">def</span> <span class="nf">get_mixture_components</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">bandwidth</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns an array containing the mixture components, i.e., the KDE functions for each class.</span>
|
||||
|
||||
|
|
@ -144,15 +135,11 @@
|
|||
<span class="sd"> :param bandwidth: float, the bandwidth of the kernel</span>
|
||||
<span class="sd"> :return: a list of KernelDensity objects, each fitted with the corresponding class-specific covariates</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">get_kde_function</span><span class="p">(</span><span class="n">X</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="n">cat</span><span class="p">],</span> <span class="n">bandwidth</span><span class="p">)</span> <span class="k">for</span> <span class="n">cat</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_classes</span><span class="p">)]</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">get_kde_function</span><span class="p">(</span><span class="n">X</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="n">cat</span><span class="p">],</span> <span class="n">bandwidth</span><span class="p">)</span> <span class="k">for</span> <span class="n">cat</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_classes</span><span class="p">)]</span></div></div>
|
||||
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEyML">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyML">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">KDEyML</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">KDEBase</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyML"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyML">[docs]</a><span class="k">class</span> <span class="nc">KDEyML</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">KDEBase</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Kernel Density Estimation model for quantification (KDEy) relying on the Kullback-Leibler divergence (KLD) as</span>
|
||||
<span class="sd"> the divergence measure to be minimized. This method was first proposed in the paper</span>
|
||||
|
|
@ -199,16 +186,11 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">n_jobs</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="o">=</span><span class="n">random_state</span>
|
||||
|
||||
<div class="viewcode-block" id="KDEyML.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyML.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyML.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyML.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mix_densities</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_mixture_components</span><span class="p">(</span><span class="o">*</span><span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">n_classes</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">bandwidth</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEyML.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyML.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyML.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyML.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Searches for the mixture model parameter (the sought prevalence values) that maximizes the likelihood</span>
|
||||
<span class="sd"> of the data (i.e., that minimizes the negative log-likelihood)</span>
|
||||
|
|
@ -226,14 +208,10 @@
|
|||
<span class="n">test_loglikelihood</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">test_mixture_likelihood</span> <span class="o">+</span> <span class="n">epsilon</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">test_loglikelihood</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">neg_loglikelihood</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">neg_loglikelihood</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEyHD">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyHD">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">KDEyHD</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">KDEBase</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyHD"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyHD">[docs]</a><span class="k">class</span> <span class="nc">KDEyHD</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">KDEBase</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Kernel Density Estimation model for quantification (KDEy) relying on the squared Hellinger Disntace (HD) as</span>
|
||||
<span class="sd"> the divergence measure to be minimized. This method was first proposed in the paper</span>
|
||||
|
|
@ -290,9 +268,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="o">=</span><span class="n">random_state</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">montecarlo_trials</span> <span class="o">=</span> <span class="n">montecarlo_trials</span>
|
||||
|
||||
<div class="viewcode-block" id="KDEyHD.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyHD.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyHD.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyHD.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mix_densities</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_mixture_components</span><span class="p">(</span><span class="o">*</span><span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">n_classes</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">bandwidth</span><span class="p">)</span>
|
||||
|
||||
<span class="n">N</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">montecarlo_trials</span>
|
||||
|
|
@ -304,10 +280,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEyHD.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyHD.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyHD.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyHD.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="c1"># we retain all n*N examples (sampled from a mixture with uniform parameter), and then</span>
|
||||
<span class="c1"># apply importance sampling (IS). In this version we compute D(p_alpha||q) with IS</span>
|
||||
<span class="n">n_classes</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mix_densities</span><span class="p">)</span>
|
||||
|
|
@ -336,14 +309,10 @@
|
|||
<span class="n">ps_div_qs</span> <span class="o">=</span> <span class="n">prev</span> <span class="o">@</span> <span class="n">fracs</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span> <span class="n">f</span><span class="p">(</span><span class="n">ps_div_qs</span><span class="p">)</span> <span class="o">*</span> <span class="n">iw</span> <span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">divergence</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">divergence</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEyCS">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">KDEyCS</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyCS"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS">[docs]</a><span class="k">class</span> <span class="nc">KDEyCS</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Kernel Density Estimation model for quantification (KDEy) relying on the Cauchy-Schwarz divergence (CS) as</span>
|
||||
<span class="sd"> the divergence measure to be minimized. This method was first proposed in the paper</span>
|
||||
|
|
@ -387,9 +356,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">bandwidth</span> <span class="o">=</span> <span class="n">bandwidth</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">n_jobs</span>
|
||||
|
||||
<div class="viewcode-block" id="KDEyCS.gram_matrix_mix_sum">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS.gram_matrix_mix_sum">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">gram_matrix_mix_sum</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">Y</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyCS.gram_matrix_mix_sum"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS.gram_matrix_mix_sum">[docs]</a> <span class="k">def</span> <span class="nf">gram_matrix_mix_sum</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">Y</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="c1"># this adapts the output of the rbf_kernel function (pairwise evaluations of Gaussian kernels k(x,y))</span>
|
||||
<span class="c1"># to contain pairwise evaluations of N(x|mu,Sigma1+Sigma2) with mu=y and Sigma1 and Sigma2 are </span>
|
||||
<span class="c1"># two "scalar matrices" (h^2)*I each, so Sigma1+Sigma2 has scalar 2(h^2) (h is the bandwidth)</span>
|
||||
|
|
@ -401,10 +368,7 @@
|
|||
<span class="n">gram</span> <span class="o">=</span> <span class="n">norm_factor</span> <span class="o">*</span> <span class="n">rbf_kernel</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">Y</span><span class="p">,</span> <span class="n">gamma</span><span class="o">=</span><span class="n">gamma</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">gram</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEyCS.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyCS.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
|
||||
<span class="n">P</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">n_classes</span>
|
||||
|
|
@ -435,10 +399,7 @@
|
|||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KDEyCS.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="KDEyCS.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._kdey.KDEyCS.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="n">Ptr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">Ptr</span>
|
||||
<span class="n">Pte</span> <span class="o">=</span> <span class="n">posteriors</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">ytr</span>
|
||||
|
|
@ -467,9 +428,7 @@
|
|||
<span class="n">partB</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">alpha_ratio</span> <span class="o">@</span> <span class="n">tr_tr_sums</span> <span class="o">@</span> <span class="n">alpha_ratio</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">partA</span> <span class="o">+</span> <span class="n">partB</span> <span class="c1">#+ partC</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">divergence</span><span class="p">,</span> <span class="n">n</span><span class="p">)</span></div>
|
||||
</div>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">divergence</span><span class="p">,</span> <span class="n">n</span><span class="p">)</span></div></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.method._neural — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
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<link rel="index" title="Index" href="../../../genindex.html" />
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<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
|
@ -84,9 +85,7 @@
|
|||
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="kn">import</span> <span class="n">tqdm</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="QuaNetTrainer">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">QuaNetTrainer</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetTrainer"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer">[docs]</a><span class="k">class</span> <span class="nc">QuaNetTrainer</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implementation of `QuaNet <https://dl.acm.org/doi/abs/10.1145/3269206.3269287>`_, a neural network for</span>
|
||||
<span class="sd"> quantification. This implementation uses `PyTorch <https://pytorch.org/>`_ and can take advantage of GPU</span>
|
||||
|
|
@ -185,9 +184,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">__check_params_colision</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">quanet_params</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">get_params</span><span class="p">())</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_classes_</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="QuaNetTrainer.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetTrainer.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Trains QuaNet.</span>
|
||||
|
||||
|
|
@ -266,7 +263,6 @@
|
|||
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_get_aggregative_estims</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">):</span>
|
||||
<span class="n">label_predictions</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">posteriors</span><span class="p">,</span> <span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">prevs_estim</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
|
@ -278,9 +274,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="n">prevs_estim</span>
|
||||
|
||||
<div class="viewcode-block" id="QuaNetTrainer.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetTrainer.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="n">posteriors</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">predict_proba</span><span class="p">(</span><span class="n">instances</span><span class="p">)</span>
|
||||
<span class="n">embeddings</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">instances</span><span class="p">)</span>
|
||||
<span class="n">quant_estims</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_aggregative_estims</span><span class="p">(</span><span class="n">posteriors</span><span class="p">)</span>
|
||||
|
|
@ -292,7 +286,6 @@
|
|||
<span class="n">prevalence</span> <span class="o">=</span> <span class="n">prevalence</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span><span class="o">.</span><span class="n">flatten</span><span class="p">()</span>
|
||||
<span class="k">return</span> <span class="n">prevalence</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_epoch</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">,</span> <span class="n">iterations</span><span class="p">,</span> <span class="n">epoch</span><span class="p">,</span> <span class="n">early_stop</span><span class="p">,</span> <span class="n">train</span><span class="p">):</span>
|
||||
<span class="n">mse_loss</span> <span class="o">=</span> <span class="n">MSELoss</span><span class="p">()</span>
|
||||
|
||||
|
|
@ -343,17 +336,12 @@
|
|||
<span class="sa">f</span><span class="s1">'val-mseloss=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">status</span><span class="p">[</span><span class="s2">"va-loss"</span><span class="p">]</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1"> val-maeloss=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">status</span><span class="p">[</span><span class="s2">"va-mae"</span><span class="p">]</span><span class="si">:</span><span class="s1">.5f</span><span class="si">}</span><span class="s1"> '</span>
|
||||
<span class="sa">f</span><span class="s1">'patience=</span><span class="si">{</span><span class="n">early_stop</span><span class="o">.</span><span class="n">patience</span><span class="si">}</span><span class="s1">/</span><span class="si">{</span><span class="n">early_stop</span><span class="o">.</span><span class="n">PATIENCE_LIMIT</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="QuaNetTrainer.get_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.get_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetTrainer.get_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.get_params">[docs]</a> <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="n">classifier_params</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">get_params</span><span class="p">()</span>
|
||||
<span class="n">classifier_params</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'classifier__'</span><span class="o">+</span><span class="n">k</span><span class="p">:</span><span class="n">v</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">classifier_params</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
|
||||
<span class="k">return</span> <span class="p">{</span><span class="o">**</span><span class="n">classifier_params</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">quanet_params</span><span class="p">}</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="QuaNetTrainer.set_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.set_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetTrainer.set_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.set_params">[docs]</a> <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="n">learner_params</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">parameters</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
|
||||
<span class="k">if</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">quanet_params</span><span class="p">:</span>
|
||||
|
|
@ -364,7 +352,6 @@
|
|||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'unknown parameter '</span><span class="p">,</span> <span class="n">key</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="o">**</span><span class="n">learner_params</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__check_params_colision</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">quanet_params</span><span class="p">,</span> <span class="n">learner_params</span><span class="p">):</span>
|
||||
<span class="n">quanet_keys</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">quanet_params</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
|
||||
<span class="n">learner_keys</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">learner_params</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
|
||||
|
|
@ -373,34 +360,25 @@
|
|||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'the use of parameters </span><span class="si">{</span><span class="n">intersection</span><span class="si">}</span><span class="s1"> is ambiguous sine those can refer to '</span>
|
||||
<span class="sa">f</span><span class="s1">'the parameters of QuaNet or the learner </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="QuaNetTrainer.clean_checkpoint">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.clean_checkpoint">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">clean_checkpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetTrainer.clean_checkpoint"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.clean_checkpoint">[docs]</a> <span class="k">def</span> <span class="nf">clean_checkpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Removes the checkpoint</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">os</span><span class="o">.</span><span class="n">remove</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">checkpoint</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="QuaNetTrainer.clean_checkpoint_dir">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.clean_checkpoint_dir">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">clean_checkpoint_dir</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetTrainer.clean_checkpoint_dir"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetTrainer.clean_checkpoint_dir">[docs]</a> <span class="k">def</span> <span class="nf">clean_checkpoint_dir</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Removes anything contained in the checkpoint directory</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="kn">import</span> <span class="nn">shutil</span>
|
||||
<span class="n">shutil</span><span class="o">.</span><span class="n">rmtree</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">checkpointdir</span><span class="p">,</span> <span class="n">ignore_errors</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">classes_</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_classes_</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mae_loss">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.mae_loss">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">mae_loss</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="mae_loss"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.mae_loss">[docs]</a><span class="k">def</span> <span class="nf">mae_loss</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Torch-like wrapper for the Mean Absolute Error</span>
|
||||
|
||||
|
|
@ -411,10 +389,7 @@
|
|||
<span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">output</span> <span class="o">-</span> <span class="n">target</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="QuaNetModule">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetModule">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">QuaNetModule</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetModule"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetModule">[docs]</a><span class="k">class</span> <span class="nc">QuaNetModule</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements the `QuaNet <https://dl.acm.org/doi/abs/10.1145/3269206.3269287>`_ forward pass.</span>
|
||||
<span class="sd"> See :class:`QuaNetTrainer` for training QuaNet.</span>
|
||||
|
|
@ -477,9 +452,7 @@
|
|||
<span class="n">var_hidden</span><span class="p">,</span> <span class="n">var_cell</span> <span class="o">=</span> <span class="n">var_hidden</span><span class="o">.</span><span class="n">cuda</span><span class="p">(),</span> <span class="n">var_cell</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
|
||||
<span class="k">return</span> <span class="n">var_hidden</span><span class="p">,</span> <span class="n">var_cell</span>
|
||||
|
||||
<div class="viewcode-block" id="QuaNetModule.forward">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetModule.forward">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">doc_embeddings</span><span class="p">,</span> <span class="n">doc_posteriors</span><span class="p">,</span> <span class="n">statistics</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="QuaNetModule.forward"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._neural.QuaNetModule.forward">[docs]</a> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">doc_embeddings</span><span class="p">,</span> <span class="n">doc_posteriors</span><span class="p">,</span> <span class="n">statistics</span><span class="p">):</span>
|
||||
<span class="n">device</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span>
|
||||
<span class="n">doc_embeddings</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">as_tensor</span><span class="p">(</span><span class="n">doc_embeddings</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">)</span>
|
||||
<span class="n">doc_posteriors</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">as_tensor</span><span class="p">(</span><span class="n">doc_posteriors</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">)</span>
|
||||
|
|
@ -509,9 +482,7 @@
|
|||
<span class="n">logits</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">output</span><span class="p">(</span><span class="n">abstracted</span><span class="p">)</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">prevalence</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">softmax</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">prevalence</span></div>
|
||||
</div>
|
||||
|
||||
<span class="k">return</span> <span class="n">prevalence</span></div></div>
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
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<title>quapy.method._threshold_optim — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
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@ -80,9 +81,7 @@
|
|||
<span class="kn">from</span> <span class="nn">quapy.method.aggregative</span> <span class="kn">import</span> <span class="n">BinaryAggregativeQuantifier</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ThresholdOptimization">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">ThresholdOptimization</span><span class="p">(</span><span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ThresholdOptimization"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization">[docs]</a><span class="k">class</span> <span class="nc">ThresholdOptimization</span><span class="p">(</span><span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Abstract class of Threshold Optimization variants for :class:`ACC` as proposed by</span>
|
||||
<span class="sd"> `Forman 2006 <https://dl.acm.org/doi/abs/10.1145/1150402.1150423>`_ and</span>
|
||||
|
|
@ -106,9 +105,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">val_split</span> <span class="o">=</span> <span class="n">val_split</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">_get_njobs</span><span class="p">(</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ThresholdOptimization.condition">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.condition">[docs]</a>
|
||||
<span class="nd">@abstractmethod</span>
|
||||
<div class="viewcode-block" id="ThresholdOptimization.condition"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.condition">[docs]</a> <span class="nd">@abstractmethod</span>
|
||||
<span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements the criterion according to which the threshold should be selected.</span>
|
||||
|
|
@ -120,10 +117,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="o">...</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ThresholdOptimization.discard">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.discard">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">discard</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">bool</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="ThresholdOptimization.discard"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.discard">[docs]</a> <span class="k">def</span> <span class="nf">discard</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">bool</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Indicates whether a combination of tpr and fpr should be discarded</span>
|
||||
|
||||
|
|
@ -134,7 +128,6 @@
|
|||
<span class="k">return</span> <span class="p">(</span><span class="n">tpr</span> <span class="o">-</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_eval_candidate_thresholds</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">decision_scores</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Seeks for the best `tpr` and `fpr` according to the score obtained at different</span>
|
||||
|
|
@ -170,9 +163,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="n">candidates</span>
|
||||
|
||||
<div class="viewcode-block" id="ThresholdOptimization.aggregate_with_threshold">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.aggregate_with_threshold">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate_with_threshold</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">,</span> <span class="n">tprs</span><span class="p">,</span> <span class="n">fprs</span><span class="p">,</span> <span class="n">thresholds</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ThresholdOptimization.aggregate_with_threshold"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.aggregate_with_threshold">[docs]</a> <span class="k">def</span> <span class="nf">aggregate_with_threshold</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">,</span> <span class="n">tprs</span><span class="p">,</span> <span class="n">fprs</span><span class="p">,</span> <span class="n">thresholds</span><span class="p">):</span>
|
||||
<span class="c1"># This function performs the adjusted count for given tpr, fpr, and threshold.</span>
|
||||
<span class="c1"># Note that, due to broadcasting, tprs, fprs, and thresholds could be arrays of length > 1</span>
|
||||
<span class="n">prevs_estims</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">[:,</span> <span class="kc">None</span><span class="p">]</span> <span class="o">>=</span> <span class="n">thresholds</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
|
|
@ -180,7 +171,6 @@
|
|||
<span class="n">prevs_estims</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">as_binary_prevalence</span><span class="p">(</span><span class="n">prevs_estims</span><span class="p">,</span> <span class="n">clip_if_necessary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">prevs_estims</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_compute_table</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">y_</span><span class="p">):</span>
|
||||
<span class="n">TP</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">y</span> <span class="o">==</span> <span class="n">y_</span><span class="p">,</span> <span class="n">y</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">pos_label</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
|
||||
<span class="n">FP</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">y</span> <span class="o">!=</span> <span class="n">y_</span><span class="p">,</span> <span class="n">y</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">neg_label</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
|
||||
|
|
@ -198,27 +188,18 @@
|
|||
<span class="k">return</span> <span class="mi">0</span>
|
||||
<span class="k">return</span> <span class="n">FP</span> <span class="o">/</span> <span class="p">(</span><span class="n">FP</span> <span class="o">+</span> <span class="n">TN</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ThresholdOptimization.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ThresholdOptimization.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="n">decision_scores</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span>
|
||||
<span class="c1"># the standard behavior is to keep the best threshold only</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">tpr</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fpr</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">threshold</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_eval_candidate_thresholds</span><span class="p">(</span><span class="n">decision_scores</span><span class="p">,</span> <span class="n">y</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ThresholdOptimization.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ThresholdOptimization.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.ThresholdOptimization.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="c1"># the standard behavior is to compute the adjusted count using the best threshold found</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">aggregate_with_threshold</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tpr</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fpr</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">threshold</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">aggregate_with_threshold</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tpr</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fpr</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">threshold</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="T50">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.T50">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">T50</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="T50"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.T50">[docs]</a><span class="k">class</span> <span class="nc">T50</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Threshold Optimization variant for :class:`ACC` as proposed by</span>
|
||||
<span class="sd"> `Forman 2006 <https://dl.acm.org/doi/abs/10.1145/1150402.1150423>`_ and</span>
|
||||
|
|
@ -238,17 +219,11 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="mi">5</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="T50.condition">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.T50.condition">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">abs</span><span class="p">(</span><span class="n">tpr</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<div class="viewcode-block" id="T50.condition"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.T50.condition">[docs]</a> <span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">abs</span><span class="p">(</span><span class="n">tpr</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MAX">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MAX">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">MAX</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MAX"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MAX">[docs]</a><span class="k">class</span> <span class="nc">MAX</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Threshold Optimization variant for :class:`ACC` as proposed by</span>
|
||||
<span class="sd"> `Forman 2006 <https://dl.acm.org/doi/abs/10.1145/1150402.1150423>`_ and</span>
|
||||
|
|
@ -268,18 +243,12 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="mi">5</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="MAX.condition">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MAX.condition">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="MAX.condition"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MAX.condition">[docs]</a> <span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="c1"># MAX strives to maximize (tpr - fpr), which is equivalent to minimize (fpr - tpr)</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">fpr</span> <span class="o">-</span> <span class="n">tpr</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">fpr</span> <span class="o">-</span> <span class="n">tpr</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="X">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.X">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">X</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="X"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.X">[docs]</a><span class="k">class</span> <span class="nc">X</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Threshold Optimization variant for :class:`ACC` as proposed by</span>
|
||||
<span class="sd"> `Forman 2006 <https://dl.acm.org/doi/abs/10.1145/1150402.1150423>`_ and</span>
|
||||
|
|
@ -299,17 +268,11 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="mi">5</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="X.condition">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.X.condition">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">abs</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">tpr</span> <span class="o">+</span> <span class="n">fpr</span><span class="p">))</span></div>
|
||||
</div>
|
||||
<div class="viewcode-block" id="X.condition"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.X.condition">[docs]</a> <span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">abs</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="p">(</span><span class="n">tpr</span> <span class="o">+</span> <span class="n">fpr</span><span class="p">))</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MS">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">MS</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MS"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS">[docs]</a><span class="k">class</span> <span class="nc">MS</span><span class="p">(</span><span class="n">ThresholdOptimization</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Median Sweep. Threshold Optimization variant for :class:`ACC` as proposed by</span>
|
||||
<span class="sd"> `Forman 2006 <https://dl.acm.org/doi/abs/10.1145/1150402.1150423>`_ and</span>
|
||||
|
|
@ -328,15 +291,10 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="mi">5</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="MS.condition">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS.condition">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="MS.condition"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS.condition">[docs]</a> <span class="k">def</span> <span class="nf">condition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mi">1</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MS.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MS.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="n">decision_scores</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span>
|
||||
<span class="c1"># keeps all candidates</span>
|
||||
<span class="n">tprs_fprs_thresholds</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_eval_candidate_thresholds</span><span class="p">(</span><span class="n">decision_scores</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
|
||||
|
|
@ -345,21 +303,14 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">thresholds</span> <span class="o">=</span> <span class="n">tprs_fprs_thresholds</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MS.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MS.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="n">prevalences</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">aggregate_with_threshold</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tprs</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fprs</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">thresholds</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">prevalences</span><span class="o">.</span><span class="n">ndim</span><span class="o">==</span><span class="mi">2</span><span class="p">:</span>
|
||||
<span class="n">prevalences</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prevalences</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">prevalences</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">prevalences</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MS2">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS2">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">MS2</span><span class="p">(</span><span class="n">MS</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MS2"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS2">[docs]</a><span class="k">class</span> <span class="nc">MS2</span><span class="p">(</span><span class="n">MS</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Median Sweep 2. Threshold Optimization variant for :class:`ACC` as proposed by</span>
|
||||
<span class="sd"> `Forman 2006 <https://dl.acm.org/doi/abs/10.1145/1150402.1150423>`_ and</span>
|
||||
|
|
@ -379,12 +330,8 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="mi">5</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="MS2.discard">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS2.discard">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">discard</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">bool</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">tpr</span><span class="o">-</span><span class="n">fpr</span><span class="p">)</span> <span class="o"><=</span> <span class="mf">0.25</span></div>
|
||||
</div>
|
||||
|
||||
<div class="viewcode-block" id="MS2.discard"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method._threshold_optim.MS2.discard">[docs]</a> <span class="k">def</span> <span class="nf">discard</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">fpr</span><span class="p">)</span> <span class="o">-></span> <span class="nb">bool</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">tpr</span><span class="o">-</span><span class="n">fpr</span><span class="p">)</span> <span class="o"><=</span> <span class="mf">0.25</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.method.aggregative — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
|
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<link rel="stylesheet" type="text/css" href="../../../_static/css/theme.css" />
|
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|
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|
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<!--[if lt IE 9]>
|
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<script src="../../../_static/js/html5shiv.min.js"></script>
|
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<![endif]-->
|
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|
||||
<script src="../../../_static/jquery.js?v=5d32c60e"></script>
|
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<script src="../../../_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
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<script src="../../../_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="../../../_static/doctools.js?v=9a2dae69"></script>
|
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<script src="../../../_static/sphinx_highlight.js?v=dc90522c"></script>
|
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<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
|
||||
<script src="../../../_static/jquery.js"></script>
|
||||
<script src="../../../_static/underscore.js"></script>
|
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<script src="../../../_static/_sphinx_javascript_frameworks_compat.js"></script>
|
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<script src="../../../_static/doctools.js"></script>
|
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<script src="../../../_static/sphinx_highlight.js"></script>
|
||||
<script src="../../../_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="../../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
|
@ -93,9 +94,7 @@
|
|||
<span class="c1"># Abstract classes</span>
|
||||
<span class="c1"># ------------------------------------</span>
|
||||
|
||||
<div class="viewcode-block" id="AggregativeQuantifier">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">AggregativeQuantifier</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeQuantifier"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier">[docs]</a><span class="k">class</span> <span class="nc">AggregativeQuantifier</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Abstract class for quantification methods that base their estimations on the aggregation of classification</span>
|
||||
<span class="sd"> results. Aggregative quantifiers implement a pipeline that consists of generating classification predictions</span>
|
||||
|
|
@ -147,9 +146,7 @@
|
|||
<span class="n">empty_class_names</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">classes_</span><span class="p">[</span><span class="n">empty_classes</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'classes </span><span class="si">{</span><span class="n">empty_class_names</span><span class="si">}</span><span class="s1"> have no training examples'</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Trains the aggregative quantifier. This comes down to training a classifier and an aggregation function.</span>
|
||||
|
||||
|
|
@ -163,10 +160,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">aggregation_fit</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">,</span> <span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.classifier_fit_predict">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.classifier_fit_predict">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">classifier_fit_predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">predict_on</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.classifier_fit_predict"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.classifier_fit_predict">[docs]</a> <span class="k">def</span> <span class="nf">classifier_fit_predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">predict_on</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Trains the classifier if requested (`fit_classifier=True`) and generate the necessary predictions to</span>
|
||||
<span class="sd"> train the aggregation function.</span>
|
||||
|
|
@ -236,10 +230,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="n">predictions</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.aggregation_fit">[docs]</a>
|
||||
<span class="nd">@abstractmethod</span>
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.aggregation_fit">[docs]</a> <span class="nd">@abstractmethod</span>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Trains the aggregation function.</span>
|
||||
|
|
@ -250,7 +241,6 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="o">...</span></div>
|
||||
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">classifier</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
|
|
@ -269,9 +259,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">classifier_</span> <span class="o">=</span> <span class="n">classifier</span>
|
||||
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.classify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.classify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">classify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.classify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.classify">[docs]</a> <span class="k">def</span> <span class="nf">classify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Provides the label predictions for the given instances. The predictions should respect the format expected by</span>
|
||||
<span class="sd"> :meth:`aggregate`, e.g., posterior probabilities for probabilistic quantifiers, or crisp predictions for</span>
|
||||
|
|
@ -282,7 +270,6 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_classifier_method</span><span class="p">())(</span><span class="n">instances</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_classifier_method</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Name of the method that must be used for issuing label predictions. The default one is "decision_function".</span>
|
||||
|
|
@ -301,9 +288,7 @@
|
|||
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_classifier_method</span><span class="p">()),</span> \
|
||||
<span class="sa">f</span><span class="s2">"the method does not implement the required </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">_classifier_method</span><span class="p">()</span><span class="si">}</span><span class="s2"> method"</span>
|
||||
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Generate class prevalence estimates for the sample's instances by aggregating the label predictions generated</span>
|
||||
<span class="sd"> by the classifier.</span>
|
||||
|
|
@ -314,10 +299,7 @@
|
|||
<span class="n">classif_predictions</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classify</span><span class="p">(</span><span class="n">instances</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">aggregate</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.aggregate">[docs]</a>
|
||||
<span class="nd">@abstractmethod</span>
|
||||
<div class="viewcode-block" id="AggregativeQuantifier.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeQuantifier.aggregate">[docs]</a> <span class="nd">@abstractmethod</span>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements the aggregation of label predictions.</span>
|
||||
|
|
@ -327,7 +309,6 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="o">...</span></div>
|
||||
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">classes_</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
|
|
@ -339,10 +320,7 @@
|
|||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">classes_</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeCrispQuantifier">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeCrispQuantifier">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">AggregativeCrispQuantifier</span><span class="p">(</span><span class="n">AggregativeQuantifier</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeCrispQuantifier"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeCrispQuantifier">[docs]</a><span class="k">class</span> <span class="nc">AggregativeCrispQuantifier</span><span class="p">(</span><span class="n">AggregativeQuantifier</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Abstract class for quantification methods that base their estimations on the aggregation of crips decisions</span>
|
||||
<span class="sd"> as returned by a hard classifier. Aggregative crisp quantifiers thus extend Aggregative</span>
|
||||
|
|
@ -359,10 +337,7 @@
|
|||
<span class="k">return</span> <span class="s1">'predict'</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeSoftQuantifier">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeSoftQuantifier">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">AggregativeSoftQuantifier</span><span class="p">(</span><span class="n">AggregativeQuantifier</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeSoftQuantifier"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeSoftQuantifier">[docs]</a><span class="k">class</span> <span class="nc">AggregativeSoftQuantifier</span><span class="p">(</span><span class="n">AggregativeQuantifier</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Abstract class for quantification methods that base their estimations on the aggregation of posterior</span>
|
||||
<span class="sd"> probabilities as returned by a probabilistic classifier.</span>
|
||||
|
|
@ -401,10 +376,7 @@
|
|||
<span class="sa">f</span><span class="s1">'fit_classifier is set to False'</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="BinaryAggregativeQuantifier">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.BinaryAggregativeQuantifier">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">BinaryAggregativeQuantifier</span><span class="p">(</span><span class="n">AggregativeQuantifier</span><span class="p">,</span> <span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="BinaryAggregativeQuantifier"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.BinaryAggregativeQuantifier">[docs]</a><span class="k">class</span> <span class="nc">BinaryAggregativeQuantifier</span><span class="p">(</span><span class="n">AggregativeQuantifier</span><span class="p">,</span> <span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">pos_label</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
|
|
@ -414,20 +386,14 @@
|
|||
<span class="k">def</span> <span class="nf">neg_label</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">classes_</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="BinaryAggregativeQuantifier.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.BinaryAggregativeQuantifier.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="BinaryAggregativeQuantifier.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.BinaryAggregativeQuantifier.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_check_binary</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="p">)</span></div>
|
||||
</div>
|
||||
|
||||
<span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
<span class="c1"># Methods</span>
|
||||
<span class="c1"># ------------------------------------</span>
|
||||
<div class="viewcode-block" id="CC">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.CC">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">CC</span><span class="p">(</span><span class="n">AggregativeCrispQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="CC"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.CC">[docs]</a><span class="k">class</span> <span class="nc">CC</span><span class="p">(</span><span class="n">AggregativeCrispQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> The most basic Quantification method. One that simply classifies all instances and counts how many have been</span>
|
||||
<span class="sd"> attributed to each of the classes in order to compute class prevalence estimates.</span>
|
||||
|
|
@ -438,9 +404,7 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">classifier</span>
|
||||
|
||||
<div class="viewcode-block" id="CC.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.CC.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="CC.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.CC.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Nothing to do here!</span>
|
||||
|
||||
|
|
@ -448,24 +412,17 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="CC.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.CC.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="CC.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.CC.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Computes class prevalence estimates by counting the prevalence of each of the predicted labels.</span>
|
||||
|
||||
<span class="sd"> :param classif_predictions: array-like with label predictions</span>
|
||||
<span class="sd"> :return: `np.ndarray` of shape `(n_classes,)` with class prevalence estimates.</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">prevalence_from_labels</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">classes_</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">prevalence_from_labels</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">classes_</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ACC">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">ACC</span><span class="p">(</span><span class="n">AggregativeCrispQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ACC"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC">[docs]</a><span class="k">class</span> <span class="nc">ACC</span><span class="p">(</span><span class="n">AggregativeCrispQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `Adjusted Classify & Count <https://link.springer.com/article/10.1007/s10618-008-0097-y>`_,</span>
|
||||
<span class="sd"> the "adjusted" variant of :class:`CC`, that corrects the predictions of CC</span>
|
||||
|
|
@ -502,9 +459,7 @@
|
|||
<span class="k">def</span> <span class="nf">_check_init_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">solver</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">'exact'</span><span class="p">,</span> <span class="s1">'minimize'</span><span class="p">],</span> <span class="s2">"unknown solver; valid ones are 'exact', 'minimize'"</span>
|
||||
|
||||
<div class="viewcode-block" id="ACC.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ACC.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Estimates the misclassification rates.</span>
|
||||
|
||||
|
|
@ -514,10 +469,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">cc</span> <span class="o">=</span> <span class="n">CC</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Pte_cond_estim_</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">getPteCondEstim</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">classes_</span><span class="p">,</span> <span class="n">true_labels</span><span class="p">,</span> <span class="n">pred_labels</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ACC.getPteCondEstim">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.getPteCondEstim">[docs]</a>
|
||||
<span class="nd">@classmethod</span>
|
||||
<div class="viewcode-block" id="ACC.getPteCondEstim"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.getPteCondEstim">[docs]</a> <span class="nd">@classmethod</span>
|
||||
<span class="k">def</span> <span class="nf">getPteCondEstim</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">classes</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">y_</span><span class="p">):</span>
|
||||
<span class="c1"># estimate the matrix with entry (i,j) being the estimate of P(hat_yi|yj), that is, the probability that a</span>
|
||||
<span class="c1"># document that belongs to yj ends up being classified as belonging to yi</span>
|
||||
|
|
@ -531,17 +483,11 @@
|
|||
<span class="n">conf</span><span class="p">[:,</span> <span class="n">i</span><span class="p">]</span> <span class="o">/=</span> <span class="n">class_counts</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">conf</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ACC.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ACC.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">):</span>
|
||||
<span class="n">prevs_estim</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">cc</span><span class="o">.</span><span class="n">aggregate</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">ACC</span><span class="o">.</span><span class="n">solve_adjustment</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">Pte_cond_estim_</span><span class="p">,</span> <span class="n">prevs_estim</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">solver</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ACC.solve_adjustment">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.solve_adjustment">[docs]</a>
|
||||
<span class="nd">@classmethod</span>
|
||||
<div class="viewcode-block" id="ACC.solve_adjustment"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.ACC.solve_adjustment">[docs]</a> <span class="nd">@classmethod</span>
|
||||
<span class="k">def</span> <span class="nf">solve_adjustment</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">PteCondEstim</span><span class="p">,</span> <span class="n">prevs_estim</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'exact'</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Solves the system linear system :math:`Ax = B` with :math:`A` = `PteCondEstim` and :math:`B` = `prevs_estim`</span>
|
||||
|
|
@ -577,14 +523,10 @@
|
|||
<span class="k">def</span> <span class="nf">loss</span><span class="p">(</span><span class="n">prev</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">norm</span><span class="p">(</span><span class="n">A</span> <span class="o">@</span> <span class="n">prev</span> <span class="o">-</span> <span class="n">B</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="o">=</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">optim_minimize</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="o">=</span><span class="n">A</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="PCC">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PCC">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">PCC</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="PCC"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PCC">[docs]</a><span class="k">class</span> <span class="nc">PCC</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `Probabilistic Classify & Count <https://ieeexplore.ieee.org/abstract/document/5694031>`_,</span>
|
||||
<span class="sd"> the probabilistic variant of CC that relies on the posterior probabilities returned by a probabilistic classifier.</span>
|
||||
|
|
@ -595,9 +537,7 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">classifier</span>
|
||||
|
||||
<div class="viewcode-block" id="PCC.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PCC.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="PCC.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PCC.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Nothing to do here!</span>
|
||||
|
||||
|
|
@ -605,18 +545,11 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="PCC.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PCC.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">prevalence_from_probabilities</span><span class="p">(</span><span class="n">classif_posteriors</span><span class="p">,</span> <span class="n">binarize</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<div class="viewcode-block" id="PCC.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PCC.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">prevalence_from_probabilities</span><span class="p">(</span><span class="n">classif_posteriors</span><span class="p">,</span> <span class="n">binarize</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="PACC">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">PACC</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="PACC"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC">[docs]</a><span class="k">class</span> <span class="nc">PACC</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `Probabilistic Adjusted Classify & Count <https://ieeexplore.ieee.org/abstract/document/5694031>`_,</span>
|
||||
<span class="sd"> the probabilistic variant of ACC that relies on the posterior probabilities returned by a probabilistic classifier.</span>
|
||||
|
|
@ -652,9 +585,7 @@
|
|||
<span class="k">def</span> <span class="nf">_check_init_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">solver</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">'exact'</span><span class="p">,</span> <span class="s1">'minimize'</span><span class="p">],</span> <span class="s2">"unknown solver; valid ones are 'exact', 'minimize'"</span>
|
||||
|
||||
<div class="viewcode-block" id="PACC.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="PACC.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Estimates the misclassification rates</span>
|
||||
|
||||
|
|
@ -664,17 +595,11 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">pcc</span> <span class="o">=</span> <span class="n">PCC</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Pte_cond_estim_</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">getPteCondEstim</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">classes_</span><span class="p">,</span> <span class="n">true_labels</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="PACC.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="PACC.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<span class="n">prevs_estim</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pcc</span><span class="o">.</span><span class="n">aggregate</span><span class="p">(</span><span class="n">classif_posteriors</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">ACC</span><span class="o">.</span><span class="n">solve_adjustment</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">Pte_cond_estim_</span><span class="p">,</span> <span class="n">prevs_estim</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">solver</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="PACC.getPteCondEstim">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC.getPteCondEstim">[docs]</a>
|
||||
<span class="nd">@classmethod</span>
|
||||
<div class="viewcode-block" id="PACC.getPteCondEstim"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.PACC.getPteCondEstim">[docs]</a> <span class="nd">@classmethod</span>
|
||||
<span class="k">def</span> <span class="nf">getPteCondEstim</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">classes</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">y_</span><span class="p">):</span>
|
||||
<span class="c1"># estimate the matrix with entry (i,j) being the estimate of P(hat_yi|yj), that is, the probability that a</span>
|
||||
<span class="c1"># document that belongs to yj ends up being classified as belonging to yi</span>
|
||||
|
|
@ -685,14 +610,10 @@
|
|||
<span class="k">if</span> <span class="n">idx</span><span class="o">.</span><span class="n">any</span><span class="p">():</span>
|
||||
<span class="n">confusion</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">y_</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">confusion</span><span class="o">.</span><span class="n">T</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">confusion</span><span class="o">.</span><span class="n">T</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EMQ">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">EMQ</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EMQ"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ">[docs]</a><span class="k">class</span> <span class="nc">EMQ</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `Expectation Maximization for Quantification <https://ieeexplore.ieee.org/abstract/document/6789744>`_ (EMQ),</span>
|
||||
<span class="sd"> aka `Saerens-Latinne-Decaestecker` (SLD) algorithm.</span>
|
||||
|
|
@ -736,9 +657,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">recalib</span> <span class="o">=</span> <span class="n">recalib</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">n_jobs</span>
|
||||
|
||||
<div class="viewcode-block" id="EMQ.EMQ_BCTS">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.EMQ_BCTS">[docs]</a>
|
||||
<span class="nd">@classmethod</span>
|
||||
<div class="viewcode-block" id="EMQ.EMQ_BCTS"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.EMQ_BCTS">[docs]</a> <span class="nd">@classmethod</span>
|
||||
<span class="k">def</span> <span class="nf">EMQ_BCTS</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">classifier</span><span class="p">:</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Constructs an instance of EMQ using the best configuration found in the `Alexandari et al. paper</span>
|
||||
|
|
@ -752,7 +671,6 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">EMQ</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">val_split</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">exact_train_prev</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">recalib</span><span class="o">=</span><span class="s1">'bcts'</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="n">n_jobs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_check_init_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">val_split</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">exact_train_prev</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">recalib</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
|
|
@ -767,9 +685,7 @@
|
|||
<span class="sa">f</span><span class="s1">'indicating the number of folds for kFCV.'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">val_split</span><span class="o">=</span><span class="mi">5</span>
|
||||
|
||||
<div class="viewcode-block" id="EMQ.classify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.classify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">classify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EMQ.classify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.classify">[docs]</a> <span class="k">def</span> <span class="nf">classify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Provides the posterior probabilities for the given instances. If the classifier was required</span>
|
||||
<span class="sd"> to be recalibrated, then these posteriors are recalibrated accordingly.</span>
|
||||
|
|
@ -782,10 +698,7 @@
|
|||
<span class="n">posteriors</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calibration_function</span><span class="p">(</span><span class="n">posteriors</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">posteriors</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EMQ.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EMQ.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">recalib</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">P</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">recalib</span> <span class="o">==</span> <span class="s1">'nbvs'</span><span class="p">:</span>
|
||||
|
|
@ -810,17 +723,11 @@
|
|||
<span class="n">train_posteriors</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calibration_function</span><span class="p">(</span><span class="n">train_posteriors</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">train_prevalence</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">prevalence_from_probabilities</span><span class="p">(</span><span class="n">train_posteriors</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EMQ.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="n">EPSILON</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EMQ.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="n">EPSILON</span><span class="p">):</span>
|
||||
<span class="n">priors</span><span class="p">,</span> <span class="n">posteriors</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">EM</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">train_prevalence</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">,</span> <span class="n">epsilon</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">priors</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EMQ.predict_proba">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.predict_proba">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="n">EPSILON</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EMQ.predict_proba"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.predict_proba">[docs]</a> <span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="n">EPSILON</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the posterior probabilities updated by the EM algorithm.</span>
|
||||
|
||||
|
|
@ -832,10 +739,7 @@
|
|||
<span class="n">priors</span><span class="p">,</span> <span class="n">posteriors</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">EM</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">train_prevalence</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">,</span> <span class="n">epsilon</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">posteriors</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EMQ.EM">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.EM">[docs]</a>
|
||||
<span class="nd">@classmethod</span>
|
||||
<div class="viewcode-block" id="EMQ.EM"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.EMQ.EM">[docs]</a> <span class="nd">@classmethod</span>
|
||||
<span class="k">def</span> <span class="nf">EM</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">tr_prev</span><span class="p">,</span> <span class="n">posterior_probabilities</span><span class="p">,</span> <span class="n">epsilon</span><span class="o">=</span><span class="n">EPSILON</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Computes the `Expectation Maximization` routine.</span>
|
||||
|
|
@ -871,14 +775,10 @@
|
|||
<span class="k">if</span> <span class="ow">not</span> <span class="n">converged</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s1">'[warning] the method has reached the maximum number of iterations; it might have not converged'</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">qs</span><span class="p">,</span> <span class="n">ps</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">qs</span><span class="p">,</span> <span class="n">ps</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HDy">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.HDy">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">HDy</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="HDy"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.HDy">[docs]</a><span class="k">class</span> <span class="nc">HDy</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `Hellinger Distance y <https://www.sciencedirect.com/science/article/pii/S0020025512004069>`_ (HDy).</span>
|
||||
<span class="sd"> HDy is a probabilistic method for training binary quantifiers, that models quantification as the problem of</span>
|
||||
|
|
@ -897,9 +797,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">classifier</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">val_split</span> <span class="o">=</span> <span class="n">val_split</span>
|
||||
|
||||
<div class="viewcode-block" id="HDy.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.HDy.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="HDy.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.HDy.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Trains a HDy quantifier.</span>
|
||||
|
||||
|
|
@ -927,10 +825,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HDy.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.HDy.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="HDy.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.HDy.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<span class="c1"># "In this work, the number of bins b used in HDx and HDy was chosen from 10 to 110 in steps of 10,</span>
|
||||
<span class="c1"># and the final estimated a priori probability was taken as the median of these 11 estimates."</span>
|
||||
<span class="c1"># (González-Castro, et al., 2013).</span>
|
||||
|
|
@ -959,14 +854,10 @@
|
|||
<span class="n">prev_estimations</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">prev_selected</span><span class="p">)</span>
|
||||
|
||||
<span class="n">class1_prev</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prev_estimations</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">as_binary_prevalence</span><span class="p">(</span><span class="n">class1_prev</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">as_binary_prevalence</span><span class="p">(</span><span class="n">class1_prev</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DyS">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DyS">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">DyS</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DyS"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DyS">[docs]</a><span class="k">class</span> <span class="nc">DyS</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `DyS framework <https://ojs.aaai.org/index.php/AAAI/article/view/4376>`_ (DyS).</span>
|
||||
<span class="sd"> DyS is a generalization of HDy method, using a Ternary Search in order to find the prevalence that</span>
|
||||
|
|
@ -1007,9 +898,7 @@
|
|||
<span class="c1"># Left and right are the current bounds; the maximum is between them</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">left</span> <span class="o">+</span> <span class="n">right</span><span class="p">)</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
|
||||
<div class="viewcode-block" id="DyS.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DyS.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DyS.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DyS.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="n">Px</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span>
|
||||
<span class="n">Px</span> <span class="o">=</span> <span class="n">Px</span><span class="p">[:,</span> <span class="bp">self</span><span class="o">.</span><span class="n">pos_label</span><span class="p">]</span> <span class="c1"># takes only the P(y=+1|x)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Pxy1</span> <span class="o">=</span> <span class="n">Px</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">pos_label</span><span class="p">]</span>
|
||||
|
|
@ -1018,10 +907,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">Pxy0_density</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">histogram</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">Pxy0</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">n_bins</span><span class="p">,</span> <span class="nb">range</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">density</span><span class="o">=</span><span class="kc">True</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DyS.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DyS.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DyS.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DyS.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<span class="n">Px</span> <span class="o">=</span> <span class="n">classif_posteriors</span><span class="p">[:,</span> <span class="bp">self</span><span class="o">.</span><span class="n">pos_label</span><span class="p">]</span> <span class="c1"># takes only the P(y=+1|x)</span>
|
||||
|
||||
<span class="n">Px_test</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">histogram</span><span class="p">(</span><span class="n">Px</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">n_bins</span><span class="p">,</span> <span class="nb">range</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">density</span><span class="o">=</span><span class="kc">True</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
|
@ -1032,14 +918,10 @@
|
|||
<span class="k">return</span> <span class="n">divergence</span><span class="p">(</span><span class="n">Px_train</span><span class="p">,</span> <span class="n">Px_test</span><span class="p">)</span>
|
||||
|
||||
<span class="n">class1_prev</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_ternary_search</span><span class="p">(</span><span class="n">f</span><span class="o">=</span><span class="n">distribution_distance</span><span class="p">,</span> <span class="n">left</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">right</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tol</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">as_binary_prevalence</span><span class="p">(</span><span class="n">class1_prev</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">as_binary_prevalence</span><span class="p">(</span><span class="n">class1_prev</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SMM">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.SMM">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">SMM</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="SMM"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.SMM">[docs]</a><span class="k">class</span> <span class="nc">SMM</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">,</span> <span class="n">BinaryAggregativeQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `SMM method <https://ieeexplore.ieee.org/document/9260028>`_ (SMM).</span>
|
||||
<span class="sd"> SMM is a simplification of matching distribution methods where the representation of the examples</span>
|
||||
|
|
@ -1054,9 +936,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">classifier</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">val_split</span> <span class="o">=</span> <span class="n">val_split</span>
|
||||
|
||||
<div class="viewcode-block" id="SMM.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.SMM.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="SMM.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.SMM.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="n">Px</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">classif_predictions</span><span class="o">.</span><span class="n">Xy</span>
|
||||
<span class="n">Px</span> <span class="o">=</span> <span class="n">Px</span><span class="p">[:,</span> <span class="bp">self</span><span class="o">.</span><span class="n">pos_label</span><span class="p">]</span> <span class="c1"># takes only the P(y=+1|x)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Pxy1</span> <span class="o">=</span> <span class="n">Px</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">pos_label</span><span class="p">]</span>
|
||||
|
|
@ -1065,22 +945,15 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">Pxy0_mean</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">Pxy0</span><span class="p">)</span> <span class="c1"># equiv. FPR</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SMM.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.SMM.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="SMM.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.SMM.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_posteriors</span><span class="p">):</span>
|
||||
<span class="n">Px</span> <span class="o">=</span> <span class="n">classif_posteriors</span><span class="p">[:,</span> <span class="bp">self</span><span class="o">.</span><span class="n">pos_label</span><span class="p">]</span> <span class="c1"># takes only the P(y=+1|x)</span>
|
||||
<span class="n">Px_mean</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">Px</span><span class="p">)</span>
|
||||
|
||||
<span class="n">class1_prev</span> <span class="o">=</span> <span class="p">(</span><span class="n">Px_mean</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">Pxy0_mean</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">Pxy1_mean</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">Pxy0_mean</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">as_binary_prevalence</span><span class="p">(</span><span class="n">class1_prev</span><span class="p">,</span> <span class="n">clip_if_necessary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">as_binary_prevalence</span><span class="p">(</span><span class="n">class1_prev</span><span class="p">,</span> <span class="n">clip_if_necessary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DMy">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DMy">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">DMy</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DMy"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DMy">[docs]</a><span class="k">class</span> <span class="nc">DMy</span><span class="p">(</span><span class="n">AggregativeSoftQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Generic Distribution Matching quantifier for binary or multiclass quantification based on the space of posterior</span>
|
||||
<span class="sd"> probabilities. This implementation takes the number of bins, the divergence, and the possibility to work on CDF</span>
|
||||
|
|
@ -1135,9 +1008,7 @@
|
|||
<span class="n">distributions</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">distributions</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">distributions</span>
|
||||
|
||||
<div class="viewcode-block" id="DMy.aggregation_fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DMy.aggregation_fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DMy.aggregation_fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DMy.aggregation_fit">[docs]</a> <span class="k">def</span> <span class="nf">aggregation_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Trains the classifier (if requested) and generates the validation distributions out of the training data.</span>
|
||||
<span class="sd"> The validation distributions have shape `(n, ch, nbins)`, with `n` the number of classes, `ch` the number of</span>
|
||||
|
|
@ -1163,10 +1034,7 @@
|
|||
<span class="n">backend</span><span class="o">=</span><span class="s1">'threading'</span>
|
||||
<span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DMy.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DMy.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DMy.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.DMy.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">posteriors</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Searches for the mixture model parameter (the sought prevalence values) that yields a validation distribution</span>
|
||||
<span class="sd"> (the mixture) that best matches the test distribution, in terms of the divergence measure of choice.</span>
|
||||
|
|
@ -1186,15 +1054,11 @@
|
|||
<span class="n">divs</span> <span class="o">=</span> <span class="p">[</span><span class="n">divergence</span><span class="p">(</span><span class="n">test_distribution</span><span class="p">[</span><span class="n">ch</span><span class="p">],</span> <span class="n">mixture_distribution</span><span class="p">[</span><span class="n">ch</span><span class="p">])</span> <span class="k">for</span> <span class="n">ch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_channels</span><span class="p">)]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">divs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">argmin_prevalence</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">search</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">argmin_prevalence</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">search</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="newELM">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newELM">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">newELM</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'01'</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="newELM"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newELM">[docs]</a><span class="k">def</span> <span class="nf">newELM</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'01'</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Explicit Loss Minimization (ELM) quantifiers.</span>
|
||||
<span class="sd"> Quantifiers based on ELM represent a family of methods based on structured output learning;</span>
|
||||
|
|
@ -1221,10 +1085,7 @@
|
|||
<span class="k">return</span> <span class="n">CC</span><span class="p">(</span><span class="n">SVMperf</span><span class="p">(</span><span class="n">svmperf_base</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="n">loss</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="n">C</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="newSVMQ">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMQ">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">newSVMQ</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="newSVMQ"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMQ">[docs]</a><span class="k">def</span> <span class="nf">newSVMQ</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> SVM(Q) is an Explicit Loss Minimization (ELM) quantifier set to optimize for the `Q` loss combining a</span>
|
||||
<span class="sd"> classification-oriented loss and a quantification-oriented loss, as proposed by</span>
|
||||
|
|
@ -1249,7 +1110,6 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">newELM</span><span class="p">(</span><span class="n">svmperf_base</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'q'</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="n">C</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">newSVMKLD</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> SVM(KLD) is an Explicit Loss Minimization (ELM) quantifier set to optimize for the Kullback-Leibler Divergence</span>
|
||||
|
|
@ -1275,9 +1135,7 @@
|
|||
<span class="k">return</span> <span class="n">newELM</span><span class="p">(</span><span class="n">svmperf_base</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'kld'</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="n">C</span><span class="p">)</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="newSVMKLD">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMKLD">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">newSVMKLD</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="newSVMKLD"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMKLD">[docs]</a><span class="k">def</span> <span class="nf">newSVMKLD</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> SVM(KLD) is an Explicit Loss Minimization (ELM) quantifier set to optimize for the Kullback-Leibler Divergence</span>
|
||||
<span class="sd"> normalized via the logistic function, as proposed by</span>
|
||||
|
|
@ -1302,10 +1160,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">newELM</span><span class="p">(</span><span class="n">svmperf_base</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'nkld'</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="n">C</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="newSVMAE">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMAE">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">newSVMAE</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="newSVMAE"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMAE">[docs]</a><span class="k">def</span> <span class="nf">newSVMAE</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> SVM(KLD) is an Explicit Loss Minimization (ELM) quantifier set to optimize for the Absolute Error as first used by</span>
|
||||
<span class="sd"> `Moreo and Sebastiani, 2021 <https://arxiv.org/abs/2011.02552>`_.</span>
|
||||
|
|
@ -1329,10 +1184,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">newELM</span><span class="p">(</span><span class="n">svmperf_base</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'mae'</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="n">C</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="newSVMRAE">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMRAE">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">newSVMRAE</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="newSVMRAE"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.newSVMRAE">[docs]</a><span class="k">def</span> <span class="nf">newSVMRAE</span><span class="p">(</span><span class="n">svmperf_base</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> SVM(KLD) is an Explicit Loss Minimization (ELM) quantifier set to optimize for the Relative Absolute Error as first</span>
|
||||
<span class="sd"> used by `Moreo and Sebastiani, 2021 <https://arxiv.org/abs/2011.02552>`_.</span>
|
||||
|
|
@ -1357,10 +1209,7 @@
|
|||
<span class="k">return</span> <span class="n">newELM</span><span class="p">(</span><span class="n">svmperf_base</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s1">'mrae'</span><span class="p">,</span> <span class="n">C</span><span class="o">=</span><span class="n">C</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="OneVsAllAggregative">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.OneVsAllAggregative">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">OneVsAllAggregative</span><span class="p">(</span><span class="n">OneVsAllGeneric</span><span class="p">,</span> <span class="n">AggregativeQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OneVsAllAggregative"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.OneVsAllAggregative">[docs]</a><span class="k">class</span> <span class="nc">OneVsAllAggregative</span><span class="p">(</span><span class="n">OneVsAllGeneric</span><span class="p">,</span> <span class="n">AggregativeQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Allows any binary quantifier to perform quantification on single-label datasets.</span>
|
||||
<span class="sd"> The method maintains one binary quantifier for each class, and then l1-normalizes the outputs so that the</span>
|
||||
|
|
@ -1385,9 +1234,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">_get_njobs</span><span class="p">(</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">parallel_backend</span> <span class="o">=</span> <span class="n">parallel_backend</span>
|
||||
|
||||
<div class="viewcode-block" id="OneVsAllAggregative.classify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.OneVsAllAggregative.classify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">classify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OneVsAllAggregative.classify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.OneVsAllAggregative.classify">[docs]</a> <span class="k">def</span> <span class="nf">classify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> If the base quantifier is not probabilistic, returns a matrix of shape `(n,m,)` with `n` the number of</span>
|
||||
<span class="sd"> instances and `m` the number of classes. The entry `(i,j)` is a binary value indicating whether instance</span>
|
||||
|
|
@ -1408,14 +1255,10 @@
|
|||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">classif_predictions</span><span class="o">.</span><span class="n">T</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="OneVsAllAggregative.aggregate">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.OneVsAllAggregative.aggregate">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OneVsAllAggregative.aggregate"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.OneVsAllAggregative.aggregate">[docs]</a> <span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">):</span>
|
||||
<span class="n">prevalences</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_parallel</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_delayed_binary_aggregate</span><span class="p">,</span> <span class="n">classif_predictions</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">normalize_prevalence</span><span class="p">(</span><span class="n">prevalences</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delayed_binary_classification</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">dict_binary_quantifiers</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">classify</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
|
||||
|
||||
|
|
@ -1424,10 +1267,7 @@
|
|||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">dict_binary_quantifiers</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">aggregate</span><span class="p">(</span><span class="n">classif_predictions</span><span class="p">[:,</span> <span class="n">c</span><span class="p">])[</span><span class="mi">1</span><span class="p">]</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">AggregativeMedianEstimator</span><span class="p">(</span><span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator">[docs]</a><span class="k">class</span> <span class="nc">AggregativeMedianEstimator</span><span class="p">(</span><span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> This method is a meta-quantifier that returns, as the estimated class prevalence values, the median of the</span>
|
||||
<span class="sd"> estimation returned by differently (hyper)parameterized base quantifiers.</span>
|
||||
|
|
@ -1445,18 +1285,12 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span> <span class="o">=</span> <span class="n">random_state</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">_get_njobs</span><span class="p">(</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.get_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.get_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.get_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.get_params">[docs]</a> <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">base_quantifier</span><span class="o">.</span><span class="n">get_params</span><span class="p">(</span><span class="n">deep</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.set_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.set_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.set_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.set_params">[docs]</a> <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">base_quantifier</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="o">**</span><span class="n">params</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delayed_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">args</span><span class="p">):</span>
|
||||
<span class="k">with</span> <span class="n">qp</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">temp_seed</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">):</span>
|
||||
<span class="n">params</span><span class="p">,</span> <span class="n">training</span> <span class="o">=</span> <span class="n">args</span>
|
||||
|
|
@ -1484,9 +1318,7 @@
|
|||
<span class="k">return</span> <span class="n">model</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="kn">import</span> <span class="nn">itertools</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_check_binary</span><span class="p">(</span><span class="n">training</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
|
||||
|
|
@ -1528,14 +1360,11 @@
|
|||
<span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delayed_predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">model</span><span class="p">,</span> <span class="n">instances</span> <span class="o">=</span> <span class="n">args</span>
|
||||
<span class="k">return</span> <span class="n">model</span><span class="o">.</span><span class="n">quantify</span><span class="p">(</span><span class="n">instances</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AggregativeMedianEstimator.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.aggregative.AggregativeMedianEstimator.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="n">prev_preds</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">parallel</span><span class="p">(</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_delayed_predict</span><span class="p">,</span>
|
||||
<span class="p">((</span><span class="n">model</span><span class="p">,</span> <span class="n">instances</span><span class="p">)</span> <span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">),</span>
|
||||
|
|
@ -1543,9 +1372,7 @@
|
|||
<span class="n">n_jobs</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span><span class="p">,</span>
|
||||
<span class="n">backend</span><span class="o">=</span><span class="s1">'threading'</span>
|
||||
<span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></div>
|
||||
</div>
|
||||
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
<span class="c1">#---------------------------------------------------------------</span>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.method.base — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css?v=92fd9be5" />
|
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<link rel="stylesheet" type="text/css" href="../../../_static/css/theme.css?v=19f00094" />
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<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
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<link rel="stylesheet" type="text/css" href="../../../_static/css/theme.css" />
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<script src="../../../_static/js/html5shiv.min.js"></script>
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<![endif]-->
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<script src="../../../_static/jquery.js?v=5d32c60e"></script>
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<script src="../../../_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
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<script src="../../../_static/documentation_options.js?v=22607128"></script>
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<script src="../../../_static/doctools.js?v=9a2dae69"></script>
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<script src="../../../_static/sphinx_highlight.js?v=dc90522c"></script>
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<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
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<script src="../../../_static/jquery.js"></script>
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<script src="../../../_static/underscore.js"></script>
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<script src="../../../_static/_sphinx_javascript_frameworks_compat.js"></script>
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<script src="../../../_static/doctools.js"></script>
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<script src="../../../_static/js/theme.js"></script>
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<link rel="index" title="Index" href="../../../genindex.html" />
|
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<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
|
@ -83,18 +84,14 @@
|
|||
|
||||
<span class="c1"># Base Quantifier abstract class</span>
|
||||
<span class="c1"># ------------------------------------</span>
|
||||
<div class="viewcode-block" id="BaseQuantifier">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BaseQuantifier">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">BaseQuantifier</span><span class="p">(</span><span class="n">BaseEstimator</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="BaseQuantifier"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BaseQuantifier">[docs]</a><span class="k">class</span> <span class="nc">BaseQuantifier</span><span class="p">(</span><span class="n">BaseEstimator</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Abstract Quantifier. A quantifier is defined as an object of a class that implements the method :meth:`fit` on</span>
|
||||
<span class="sd"> :class:`quapy.data.base.LabelledCollection`, the method :meth:`quantify`, and the :meth:`set_params` and</span>
|
||||
<span class="sd"> :meth:`get_params` for model selection (see :meth:`quapy.model_selection.GridSearchQ`)</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<div class="viewcode-block" id="BaseQuantifier.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BaseQuantifier.fit">[docs]</a>
|
||||
<span class="nd">@abstractmethod</span>
|
||||
<div class="viewcode-block" id="BaseQuantifier.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BaseQuantifier.fit">[docs]</a> <span class="nd">@abstractmethod</span>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Trains a quantifier.</span>
|
||||
|
|
@ -104,10 +101,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="o">...</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="BaseQuantifier.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BaseQuantifier.quantify">[docs]</a>
|
||||
<span class="nd">@abstractmethod</span>
|
||||
<div class="viewcode-block" id="BaseQuantifier.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BaseQuantifier.quantify">[docs]</a> <span class="nd">@abstractmethod</span>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Generate class prevalence estimates for the sample's instances</span>
|
||||
|
|
@ -115,14 +109,10 @@
|
|||
<span class="sd"> :param instances: array-like</span>
|
||||
<span class="sd"> :return: `np.ndarray` of shape `(n_classes,)` with class prevalence estimates.</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="o">...</span></div>
|
||||
</div>
|
||||
<span class="o">...</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="BinaryQuantifier">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BinaryQuantifier">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">BinaryQuantifier</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="BinaryQuantifier"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.BinaryQuantifier">[docs]</a><span class="k">class</span> <span class="nc">BinaryQuantifier</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Abstract class of binary quantifiers, i.e., quantifiers estimating class prevalence values for only two classes</span>
|
||||
<span class="sd"> (typically, to be interpreted as one class and its complement).</span>
|
||||
|
|
@ -133,17 +123,11 @@
|
|||
<span class="sa">f</span><span class="s1">'Use the class OneVsAll to enable </span><span class="si">{</span><span class="n">quantifier_name</span><span class="si">}</span><span class="s1"> work on single-label data.'</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="OneVsAll">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAll">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">OneVsAll</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="OneVsAll"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAll">[docs]</a><span class="k">class</span> <span class="nc">OneVsAll</span><span class="p">:</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="newOneVsAll">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.newOneVsAll">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">newOneVsAll</span><span class="p">(</span><span class="n">binary_quantifier</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="newOneVsAll"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.newOneVsAll">[docs]</a><span class="k">def</span> <span class="nf">newOneVsAll</span><span class="p">(</span><span class="n">binary_quantifier</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">binary_quantifier</span><span class="p">,</span> <span class="n">BaseQuantifier</span><span class="p">),</span> \
|
||||
<span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">binary_quantifier</span><span class="si">}</span><span class="s1"> does not seem to be a Quantifier'</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">binary_quantifier</span><span class="p">,</span> <span class="n">qp</span><span class="o">.</span><span class="n">method</span><span class="o">.</span><span class="n">aggregative</span><span class="o">.</span><span class="n">AggregativeQuantifier</span><span class="p">):</span>
|
||||
|
|
@ -152,10 +136,7 @@
|
|||
<span class="k">return</span> <span class="n">OneVsAllGeneric</span><span class="p">(</span><span class="n">binary_quantifier</span><span class="p">,</span> <span class="n">n_jobs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="OneVsAllGeneric">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAllGeneric">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">OneVsAllGeneric</span><span class="p">(</span><span class="n">OneVsAll</span><span class="p">,</span> <span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OneVsAllGeneric"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAllGeneric">[docs]</a><span class="k">class</span> <span class="nc">OneVsAllGeneric</span><span class="p">(</span><span class="n">OneVsAll</span><span class="p">,</span> <span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Allows any binary quantifier to perform quantification on single-label datasets. The method maintains one binary</span>
|
||||
<span class="sd"> quantifier for each class, and then l1-normalizes the outputs so that the class prevelence values sum up to 1.</span>
|
||||
|
|
@ -170,9 +151,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">binary_quantifier</span> <span class="o">=</span> <span class="n">binary_quantifier</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">_get_njobs</span><span class="p">(</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="OneVsAllGeneric.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAllGeneric.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OneVsAllGeneric.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAllGeneric.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">fit_classifier</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="k">assert</span> <span class="ow">not</span> <span class="n">data</span><span class="o">.</span><span class="n">binary</span><span class="p">,</span> <span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1"> expect non-binary data'</span>
|
||||
<span class="k">assert</span> <span class="n">fit_classifier</span> <span class="o">==</span> <span class="kc">True</span><span class="p">,</span> <span class="s1">'fit_classifier must be True'</span>
|
||||
|
||||
|
|
@ -180,7 +159,6 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">_parallel</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_delayed_binary_fit</span><span class="p">,</span> <span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_parallel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span>
|
||||
<span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span><span class="p">,</span> <span class="n">backend</span><span class="o">=</span><span class="s1">'threading'</span><span class="p">)(</span>
|
||||
|
|
@ -188,13 +166,10 @@
|
|||
<span class="p">)</span>
|
||||
<span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="OneVsAllGeneric.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAllGeneric.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OneVsAllGeneric.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.base.OneVsAllGeneric.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="n">prevalences</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_parallel</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_delayed_binary_predict</span><span class="p">,</span> <span class="n">instances</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">qp</span><span class="o">.</span><span class="n">functional</span><span class="o">.</span><span class="n">normalize_prevalence</span><span class="p">(</span><span class="n">prevalences</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">classes_</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dict_binary_quantifiers</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
|
||||
|
|
@ -205,7 +180,6 @@
|
|||
<span class="k">def</span> <span class="nf">_delayed_binary_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">bindata</span> <span class="o">=</span> <span class="n">LabelledCollection</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">instances</span><span class="p">,</span> <span class="n">data</span><span class="o">.</span><span class="n">labels</span> <span class="o">==</span> <span class="n">c</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="kc">False</span><span class="p">,</span> <span class="kc">True</span><span class="p">])</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">dict_binary_quantifiers</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">bindata</span><span class="p">)</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.method.meta — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="../../../_static/css/theme.css" />
|
||||
|
||||
|
||||
<!--[if lt IE 9]>
|
||||
<script src="../../../_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
||||
|
||||
<script src="../../../_static/jquery.js?v=5d32c60e"></script>
|
||||
<script src="../../../_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
||||
<script src="../../../_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="../../../_static/doctools.js?v=9a2dae69"></script>
|
||||
<script src="../../../_static/sphinx_highlight.js?v=dc90522c"></script>
|
||||
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
|
||||
<script src="../../../_static/jquery.js"></script>
|
||||
<script src="../../../_static/underscore.js"></script>
|
||||
<script src="../../../_static/_sphinx_javascript_frameworks_compat.js"></script>
|
||||
<script src="../../../_static/doctools.js"></script>
|
||||
<script src="../../../_static/sphinx_highlight.js"></script>
|
||||
<script src="../../../_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="../../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
|
@ -98,9 +99,7 @@
|
|||
<span class="n">QuaNet</span> <span class="o">=</span> <span class="s2">"QuaNet is not available due to missing torch package"</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator2">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">MedianEstimator2</span><span class="p">(</span><span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator2"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2">[docs]</a><span class="k">class</span> <span class="nc">MedianEstimator2</span><span class="p">(</span><span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> This method is a meta-quantifier that returns, as the estimated class prevalence values, the median of the</span>
|
||||
<span class="sd"> estimation returned by differently (hyper)parameterized base quantifiers.</span>
|
||||
|
|
@ -118,18 +117,12 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span> <span class="o">=</span> <span class="n">random_state</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">_get_njobs</span><span class="p">(</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator2.get_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.get_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator2.get_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.get_params">[docs]</a> <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">base_quantifier</span><span class="o">.</span><span class="n">get_params</span><span class="p">(</span><span class="n">deep</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator2.set_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.set_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator2.set_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.set_params">[docs]</a> <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">base_quantifier</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="o">**</span><span class="n">params</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delayed_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">args</span><span class="p">):</span>
|
||||
<span class="k">with</span> <span class="n">qp</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">temp_seed</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">):</span>
|
||||
<span class="n">params</span><span class="p">,</span> <span class="n">training</span> <span class="o">=</span> <span class="n">args</span>
|
||||
|
|
@ -138,9 +131,7 @@
|
|||
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">training</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">model</span>
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator2.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator2.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_check_binary</span><span class="p">(</span><span class="n">training</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
|
||||
|
||||
<span class="n">configs</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">model_selection</span><span class="o">.</span><span class="n">expand_grid</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">param_grid</span><span class="p">)</span>
|
||||
|
|
@ -152,14 +143,11 @@
|
|||
<span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delayed_predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">model</span><span class="p">,</span> <span class="n">instances</span> <span class="o">=</span> <span class="n">args</span>
|
||||
<span class="k">return</span> <span class="n">model</span><span class="o">.</span><span class="n">quantify</span><span class="p">(</span><span class="n">instances</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator2.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator2.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator2.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="n">prev_preds</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">parallel</span><span class="p">(</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_delayed_predict</span><span class="p">,</span>
|
||||
<span class="p">((</span><span class="n">model</span><span class="p">,</span> <span class="n">instances</span><span class="p">)</span> <span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">),</span>
|
||||
|
|
@ -167,14 +155,10 @@
|
|||
<span class="n">n_jobs</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span>
|
||||
<span class="p">)</span>
|
||||
<span class="n">prev_preds</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">MedianEstimator</span><span class="p">(</span><span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator">[docs]</a><span class="k">class</span> <span class="nc">MedianEstimator</span><span class="p">(</span><span class="n">BinaryQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> This method is a meta-quantifier that returns, as the estimated class prevalence values, the median of the</span>
|
||||
<span class="sd"> estimation returned by differently (hyper)parameterized base quantifiers.</span>
|
||||
|
|
@ -192,18 +176,12 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span> <span class="o">=</span> <span class="n">random_state</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">_get_njobs</span><span class="p">(</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator.get_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.get_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator.get_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.get_params">[docs]</a> <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">base_quantifier</span><span class="o">.</span><span class="n">get_params</span><span class="p">(</span><span class="n">deep</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator.set_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.set_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator.set_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.set_params">[docs]</a> <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">base_quantifier</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="o">**</span><span class="n">params</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delayed_fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">args</span><span class="p">):</span>
|
||||
<span class="k">with</span> <span class="n">qp</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">temp_seed</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">):</span>
|
||||
<span class="n">params</span><span class="p">,</span> <span class="n">training</span> <span class="o">=</span> <span class="n">args</span>
|
||||
|
|
@ -229,9 +207,7 @@
|
|||
<span class="k">return</span> <span class="n">model</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_check_binary</span><span class="p">(</span><span class="n">training</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base_quantifier</span><span class="p">,</span> <span class="n">AggregativeQuantifier</span><span class="p">):</span>
|
||||
|
|
@ -269,14 +245,11 @@
|
|||
<span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delayed_predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">model</span><span class="p">,</span> <span class="n">instances</span> <span class="o">=</span> <span class="n">args</span>
|
||||
<span class="k">return</span> <span class="n">model</span><span class="o">.</span><span class="n">quantify</span><span class="p">(</span><span class="n">instances</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="MedianEstimator.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MedianEstimator.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.MedianEstimator.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="n">prev_preds</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">parallel</span><span class="p">(</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_delayed_predict</span><span class="p">,</span>
|
||||
<span class="p">((</span><span class="n">model</span><span class="p">,</span> <span class="n">instances</span><span class="p">)</span> <span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">),</span>
|
||||
|
|
@ -285,14 +258,10 @@
|
|||
<span class="n">asarray</span><span class="o">=</span><span class="kc">False</span>
|
||||
<span class="p">)</span>
|
||||
<span class="n">prev_preds</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">median</span><span class="p">(</span><span class="n">prev_preds</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Ensemble">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">Ensemble</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="Ensemble"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble">[docs]</a><span class="k">class</span> <span class="nc">Ensemble</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<span class="n">VALID_POLICIES</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'ave'</span><span class="p">,</span> <span class="s1">'ptr'</span><span class="p">,</span> <span class="s1">'ds'</span><span class="p">}</span> <span class="o">|</span> <span class="n">qp</span><span class="o">.</span><span class="n">error</span><span class="o">.</span><span class="n">QUANTIFICATION_ERROR_NAMES</span>
|
||||
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
|
|
@ -361,9 +330,7 @@
|
|||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">verbose</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s1">'[Ensemble]'</span> <span class="o">+</span> <span class="n">msg</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="Ensemble.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">qp</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">val_split</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">qp</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">LabelledCollection</span><span class="p">,</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="Ensemble.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">qp</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">val_split</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">qp</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">LabelledCollection</span><span class="p">,</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">policy</span> <span class="o">==</span> <span class="s1">'ds'</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">data</span><span class="o">.</span><span class="n">binary</span><span class="p">:</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">'ds policy is only defined for binary quantification, but this dataset is not binary'</span><span class="p">)</span>
|
||||
|
|
@ -400,10 +367,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">_sout</span><span class="p">(</span><span class="s1">'Fit [Done]'</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Ensemble.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="Ensemble.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="n">predictions</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span>
|
||||
<span class="n">qp</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">parallel</span><span class="p">(</span><span class="n">_delayed_quantify</span><span class="p">,</span> <span class="p">((</span><span class="n">Qi</span><span class="p">,</span> <span class="n">instances</span><span class="p">)</span> <span class="k">for</span> <span class="n">Qi</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">ensemble</span><span class="p">),</span> <span class="n">n_jobs</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
<span class="p">)</span>
|
||||
|
|
@ -416,10 +380,7 @@
|
|||
<span class="n">predictions</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">predictions</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">normalize_prevalence</span><span class="p">(</span><span class="n">predictions</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Ensemble.set_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.set_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="Ensemble.set_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.set_params">[docs]</a> <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> This function should not be used within :class:`quapy.model_selection.GridSearchQ` (is here for compatibility</span>
|
||||
<span class="sd"> with the abstract class).</span>
|
||||
|
|
@ -435,10 +396,7 @@
|
|||
<span class="sa">f</span><span class="s1">'or Ensemble(Q(GridSearchCV(l))) with Q a quantifier class that has a classifier '</span>
|
||||
<span class="sa">f</span><span class="s1">'l optimized for classification (not recommended).'</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Ensemble.get_params">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.get_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="Ensemble.get_params"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.Ensemble.get_params">[docs]</a> <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> This function should not be used within :class:`quapy.model_selection.GridSearchQ` (is here for compatibility</span>
|
||||
<span class="sd"> with the abstract class).</span>
|
||||
|
|
@ -452,7 +410,6 @@
|
|||
|
||||
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_accuracy_policy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">error_name</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Selects the red_size best performant quantifiers in a static way (i.e., dropping all non-selected instances).</span>
|
||||
|
|
@ -538,10 +495,7 @@
|
|||
<span class="k">return</span> <span class="kc">False</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_probability_distribution">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.get_probability_distribution">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_probability_distribution</span><span class="p">(</span><span class="n">posterior_probabilities</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">8</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="get_probability_distribution"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.get_probability_distribution">[docs]</a><span class="k">def</span> <span class="nf">get_probability_distribution</span><span class="p">(</span><span class="n">posterior_probabilities</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">8</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Gets a histogram out of the posterior probabilities (only for the binary case).</span>
|
||||
|
||||
|
|
@ -555,7 +509,6 @@
|
|||
<span class="k">return</span> <span class="n">distribution</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_select_k</span><span class="p">(</span><span class="n">elements</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">elements</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span> <span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">order</span><span class="p">[:</span><span class="n">k</span><span class="p">]]</span>
|
||||
|
||||
|
|
@ -649,9 +602,7 @@
|
|||
<span class="sa">f</span><span class="s1">'the name of an error function in </span><span class="si">{</span><span class="n">qp</span><span class="o">.</span><span class="n">error</span><span class="o">.</span><span class="n">ERROR_NAMES</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ensembleFactory">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.ensembleFactory">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">ensembleFactory</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">base_quantifier_class</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_model_sel</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
||||
<div class="viewcode-block" id="ensembleFactory"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.ensembleFactory">[docs]</a><span class="k">def</span> <span class="nf">ensembleFactory</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">base_quantifier_class</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_model_sel</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Ensemble factory. Provides a unified interface for instantiating ensembles that can be optimized (via model</span>
|
||||
|
|
@ -702,10 +653,7 @@
|
|||
<span class="k">return</span> <span class="n">_instantiate_ensemble</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">base_quantifier_class</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">error</span><span class="p">,</span> <span class="n">param_model_sel</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ECC">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.ECC">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">ECC</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ECC"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.ECC">[docs]</a><span class="k">def</span> <span class="nf">ECC</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements an ensemble of :class:`quapy.method.aggregative.CC` quantifiers, as used by</span>
|
||||
<span class="sd"> `Pérez-Gállego et al., 2019 <https://www.sciencedirect.com/science/article/pii/S1566253517303652>`_.</span>
|
||||
|
|
@ -728,10 +676,7 @@
|
|||
<span class="k">return</span> <span class="n">ensembleFactory</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">CC</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">optim</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EACC">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EACC">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">EACC</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EACC"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EACC">[docs]</a><span class="k">def</span> <span class="nf">EACC</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements an ensemble of :class:`quapy.method.aggregative.ACC` quantifiers, as used by</span>
|
||||
<span class="sd"> `Pérez-Gállego et al., 2019 <https://www.sciencedirect.com/science/article/pii/S1566253517303652>`_.</span>
|
||||
|
|
@ -754,10 +699,7 @@
|
|||
<span class="k">return</span> <span class="n">ensembleFactory</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">ACC</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">optim</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EPACC">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EPACC">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">EPACC</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EPACC"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EPACC">[docs]</a><span class="k">def</span> <span class="nf">EPACC</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements an ensemble of :class:`quapy.method.aggregative.PACC` quantifiers.</span>
|
||||
|
||||
|
|
@ -779,10 +721,7 @@
|
|||
<span class="k">return</span> <span class="n">ensembleFactory</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">PACC</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">optim</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EHDy">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EHDy">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">EHDy</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EHDy"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EHDy">[docs]</a><span class="k">def</span> <span class="nf">EHDy</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements an ensemble of :class:`quapy.method.aggregative.HDy` quantifiers, as used by</span>
|
||||
<span class="sd"> `Pérez-Gállego et al., 2019 <https://www.sciencedirect.com/science/article/pii/S1566253517303652>`_.</span>
|
||||
|
|
@ -805,10 +744,7 @@
|
|||
<span class="k">return</span> <span class="n">ensembleFactory</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">HDy</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">optim</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EEMQ">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EEMQ">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">EEMQ</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="EEMQ"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.meta.EEMQ">[docs]</a><span class="k">def</span> <span class="nf">EEMQ</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">optim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implements an ensemble of :class:`quapy.method.aggregative.EMQ` quantifiers.</span>
|
||||
|
||||
|
|
@ -828,7 +764,6 @@
|
|||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ensembleFactory</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">EMQ</span><span class="p">,</span> <span class="n">param_grid</span><span class="p">,</span> <span class="n">optim</span><span class="p">,</span> <span class="n">param_mod_sel</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../../">
|
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|
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.method.non_aggregative — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
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|
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<script src="../../../_static/sphinx_highlight.js"></script>
|
||||
<script src="../../../_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="../../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
|
@ -79,9 +80,7 @@
|
|||
<span class="kn">import</span> <span class="nn">quapy.functional</span> <span class="k">as</span> <span class="nn">F</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MaximumLikelihoodPrevalenceEstimation">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.MaximumLikelihoodPrevalenceEstimation">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">MaximumLikelihoodPrevalenceEstimation</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MaximumLikelihoodPrevalenceEstimation"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.MaximumLikelihoodPrevalenceEstimation">[docs]</a><span class="k">class</span> <span class="nc">MaximumLikelihoodPrevalenceEstimation</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> The `Maximum Likelihood Prevalence Estimation` (MLPE) method is a lazy method that assumes there is no prior</span>
|
||||
<span class="sd"> probability shift between training and test instances (put it other way, that the i.i.d. assumpion holds).</span>
|
||||
|
|
@ -93,9 +92,7 @@
|
|||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_classes_</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="MaximumLikelihoodPrevalenceEstimation.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.MaximumLikelihoodPrevalenceEstimation.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MaximumLikelihoodPrevalenceEstimation.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.MaximumLikelihoodPrevalenceEstimation.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Computes the training prevalence and stores it.</span>
|
||||
|
||||
|
|
@ -105,24 +102,17 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">estimated_prevalence</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">prevalence</span><span class="p">()</span>
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MaximumLikelihoodPrevalenceEstimation.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.MaximumLikelihoodPrevalenceEstimation.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="MaximumLikelihoodPrevalenceEstimation.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.MaximumLikelihoodPrevalenceEstimation.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Ignores the input instances and returns, as the class prevalence estimantes, the training prevalence.</span>
|
||||
|
||||
<span class="sd"> :param instances: array-like (ignored)</span>
|
||||
<span class="sd"> :return: the class prevalence seen during training</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">estimated_prevalence</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">estimated_prevalence</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DMx">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">DMx</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DMx"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx">[docs]</a><span class="k">class</span> <span class="nc">DMx</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Generic Distribution Matching quantifier for binary or multiclass quantification based on the space of covariates.</span>
|
||||
<span class="sd"> This implementation takes the number of bins, the divergence, and the possibility to work on CDF as hyperparameters.</span>
|
||||
|
|
@ -142,9 +132,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">search</span> <span class="o">=</span> <span class="n">search</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">n_jobs</span> <span class="o">=</span> <span class="n">n_jobs</span>
|
||||
|
||||
<div class="viewcode-block" id="DMx.HDx">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx.HDx">[docs]</a>
|
||||
<span class="nd">@classmethod</span>
|
||||
<div class="viewcode-block" id="DMx.HDx"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx.HDx">[docs]</a> <span class="nd">@classmethod</span>
|
||||
<span class="k">def</span> <span class="nf">HDx</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> `Hellinger Distance x <https://www.sciencedirect.com/science/article/pii/S0020025512004069>`_ (HDx).</span>
|
||||
|
|
@ -168,7 +156,6 @@
|
|||
<span class="n">hdx</span> <span class="o">=</span> <span class="n">MedianEstimator</span><span class="p">(</span><span class="n">base_quantifier</span><span class="o">=</span><span class="n">dmx</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="n">nbins</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="n">n_jobs</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">hdx</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__get_distributions</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span>
|
||||
|
||||
<span class="n">histograms</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
|
@ -185,9 +172,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="n">distributions</span>
|
||||
|
||||
<div class="viewcode-block" id="DMx.fit">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DMx.fit"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Generates the validation distributions out of the training data (covariates).</span>
|
||||
<span class="sd"> The validation distributions have shape `(n, nfeats, nbins)`, with `n` the number of classes, `nfeats`</span>
|
||||
|
|
@ -209,10 +194,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DMx.quantify">
|
||||
<a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DMx.quantify"><a class="viewcode-back" href="../../../quapy.method.html#quapy.method.non_aggregative.DMx.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Searches for the mixture model parameter (the sought prevalence values) that yields a validation distribution</span>
|
||||
<span class="sd"> (the mixture) that best matches the test distribution, in terms of the divergence measure of choice.</span>
|
||||
|
|
@ -234,9 +216,7 @@
|
|||
<span class="n">divs</span> <span class="o">=</span> <span class="p">[</span><span class="n">divergence</span><span class="p">(</span><span class="n">test_distribution</span><span class="p">[</span><span class="n">feat</span><span class="p">],</span> <span class="n">mixture_distribution</span><span class="p">[</span><span class="n">feat</span><span class="p">])</span> <span class="k">for</span> <span class="n">feat</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_feats</span><span class="p">)]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">divs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">argmin_prevalence</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">search</span><span class="p">)</span></div>
|
||||
</div>
|
||||
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">argmin_prevalence</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">search</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.model_selection — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css" />
|
||||
|
||||
|
||||
<!--[if lt IE 9]>
|
||||
<script src="../../_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
||||
|
||||
<script src="../../_static/jquery.js?v=5d32c60e"></script>
|
||||
<script src="../../_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
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<script src="../../_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="../../_static/doctools.js?v=9a2dae69"></script>
|
||||
<script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
|
||||
<script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
|
||||
<script src="../../_static/jquery.js"></script>
|
||||
<script src="../../_static/underscore.js"></script>
|
||||
<script src="../../_static/_sphinx_javascript_frameworks_compat.js"></script>
|
||||
<script src="../../_static/doctools.js"></script>
|
||||
<script src="../../_static/sphinx_highlight.js"></script>
|
||||
<script src="../../_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../search.html" />
|
||||
|
|
@ -89,19 +90,14 @@
|
|||
<span class="kn">from</span> <span class="nn">time</span> <span class="kn">import</span> <span class="n">time</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Status">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.Status">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">Status</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="Status"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.Status">[docs]</a><span class="k">class</span> <span class="nc">Status</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span>
|
||||
<span class="n">SUCCESS</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="n">TIMEOUT</span> <span class="o">=</span> <span class="mi">2</span>
|
||||
<span class="n">INVALID</span> <span class="o">=</span> <span class="mi">3</span>
|
||||
<span class="n">ERROR</span> <span class="o">=</span> <span class="mi">4</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConfigStatus">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.ConfigStatus">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">ConfigStatus</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="ConfigStatus"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.ConfigStatus">[docs]</a><span class="k">class</span> <span class="nc">ConfigStatus</span><span class="p">:</span>
|
||||
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">params</span><span class="p">,</span> <span class="n">status</span><span class="p">,</span> <span class="n">msg</span><span class="o">=</span><span class="s1">''</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">params</span> <span class="o">=</span> <span class="n">params</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">status</span> <span class="o">=</span> <span class="n">status</span>
|
||||
|
|
@ -113,23 +109,14 @@
|
|||
<span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ConfigStatus.success">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.ConfigStatus.success">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">success</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="ConfigStatus.success"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.ConfigStatus.success">[docs]</a> <span class="k">def</span> <span class="nf">success</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">status</span> <span class="o">==</span> <span class="n">Status</span><span class="o">.</span><span class="n">SUCCESS</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConfigStatus.failed">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.ConfigStatus.failed">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">failed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">status</span> <span class="o">!=</span> <span class="n">Status</span><span class="o">.</span><span class="n">SUCCESS</span></div>
|
||||
</div>
|
||||
<div class="viewcode-block" id="ConfigStatus.failed"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.ConfigStatus.failed">[docs]</a> <span class="k">def</span> <span class="nf">failed</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">status</span> <span class="o">!=</span> <span class="n">Status</span><span class="o">.</span><span class="n">SUCCESS</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="GridSearchQ">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">GridSearchQ</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="GridSearchQ"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ">[docs]</a><span class="k">class</span> <span class="nc">GridSearchQ</span><span class="p">(</span><span class="n">BaseQuantifier</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Grid Search optimization targeting a quantification-oriented metric.</span>
|
||||
|
||||
<span class="sd"> Optimizes the hyperparameters of a quantification method, based on an evaluation method and on an evaluation</span>
|
||||
|
|
@ -296,9 +283,7 @@
|
|||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_sout</span><span class="p">(</span><span class="sa">f</span><span class="s1">'error=</span><span class="si">{</span><span class="n">status</span><span class="si">}</span><span class="s1">'</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="GridSearchQ.fit">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.fit">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="GridSearchQ.fit"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">training</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">""" Learning routine. Fits methods with all combinations of hyperparameters and selects the one minimizing</span>
|
||||
<span class="sd"> the error metric.</span>
|
||||
|
||||
|
|
@ -362,10 +347,7 @@
|
|||
|
||||
<span class="k">return</span> <span class="bp">self</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="GridSearchQ.quantify">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.quantify">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="GridSearchQ.quantify"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.quantify">[docs]</a> <span class="k">def</span> <span class="nf">quantify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instances</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Estimate class prevalence values using the best model found after calling the :meth:`fit` method.</span>
|
||||
|
||||
<span class="sd"> :param instances: sample contanining the instances</span>
|
||||
|
|
@ -375,20 +357,14 @@
|
|||
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">'best_model_'</span><span class="p">),</span> <span class="s1">'quantify called before fit'</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">best_model</span><span class="p">()</span><span class="o">.</span><span class="n">quantify</span><span class="p">(</span><span class="n">instances</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="GridSearchQ.set_params">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.set_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="GridSearchQ.set_params"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.set_params">[docs]</a> <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Sets the hyper-parameters to explore.</span>
|
||||
|
||||
<span class="sd"> :param parameters: a dictionary with keys the parameter names and values the list of values to explore</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">param_grid</span> <span class="o">=</span> <span class="n">parameters</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="GridSearchQ.get_params">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.get_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="GridSearchQ.get_params"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.get_params">[docs]</a> <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""Returns the dictionary of hyper-parameters to explore (`param_grid`)</span>
|
||||
|
||||
<span class="sd"> :param deep: Unused</span>
|
||||
|
|
@ -396,10 +372,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">param_grid</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="GridSearchQ.best_model">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.best_model">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">best_model</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="GridSearchQ.best_model"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.GridSearchQ.best_model">[docs]</a> <span class="k">def</span> <span class="nf">best_model</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the best model found after calling the :meth:`fit` method, i.e., the one trained on the combination</span>
|
||||
<span class="sd"> of hyper-parameters that minimized the error function.</span>
|
||||
|
|
@ -410,7 +383,6 @@
|
|||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">best_model_</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'best_model called before fit'</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_error_handler</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">params</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Endorses one job with two returned values: the status, and the time of execution</span>
|
||||
|
|
@ -449,10 +421,7 @@
|
|||
<span class="k">return</span> <span class="n">output</span><span class="p">,</span> <span class="n">status</span><span class="p">,</span> <span class="n">took</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="cross_val_predict">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.cross_val_predict">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">cross_val_predict</span><span class="p">(</span><span class="n">quantifier</span><span class="p">:</span> <span class="n">BaseQuantifier</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">nfolds</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="cross_val_predict"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.cross_val_predict">[docs]</a><span class="k">def</span> <span class="nf">cross_val_predict</span><span class="p">(</span><span class="n">quantifier</span><span class="p">:</span> <span class="n">BaseQuantifier</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">LabelledCollection</span><span class="p">,</span> <span class="n">nfolds</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Akin to `scikit-learn's cross_val_predict <https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_val_predict.html>`_</span>
|
||||
<span class="sd"> but for quantification.</span>
|
||||
|
|
@ -475,10 +444,7 @@
|
|||
<span class="k">return</span> <span class="n">total_prev</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="expand_grid">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.expand_grid">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">expand_grid</span><span class="p">(</span><span class="n">param_grid</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="expand_grid"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.expand_grid">[docs]</a><span class="k">def</span> <span class="nf">expand_grid</span><span class="p">(</span><span class="n">param_grid</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Expands a param_grid dictionary as a list of configurations.</span>
|
||||
<span class="sd"> Example:</span>
|
||||
|
|
@ -497,10 +463,7 @@
|
|||
<span class="k">return</span> <span class="n">configs</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="group_params">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.model_selection.group_params">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">group_params</span><span class="p">(</span><span class="n">param_grid</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="group_params"><a class="viewcode-back" href="../../quapy.html#quapy.model_selection.group_params">[docs]</a><span class="k">def</span> <span class="nf">group_params</span><span class="p">(</span><span class="n">param_grid</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Partitions a param_grid dictionary as two lists of configurations, one for the classifier-specific</span>
|
||||
<span class="sd"> hyper-parameters, and another for que quantifier-specific hyper-parameters</span>
|
||||
|
|
@ -521,7 +484,6 @@
|
|||
|
||||
<span class="k">return</span> <span class="n">classifier_configs</span><span class="p">,</span> <span class="n">quantifier_configs</span></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.protocol — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css?v=19f00094" />
|
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<link rel="stylesheet" type="text/css" href="../../_static/pygments.css" />
|
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<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css" />
|
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|
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|
||||
<!--[if lt IE 9]>
|
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<script src="../../_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
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|
||||
<script src="../../_static/jquery.js?v=5d32c60e"></script>
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<script src="../../_static/documentation_options.js?v=22607128"></script>
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<script src="../../_static/doctools.js?v=9a2dae69"></script>
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<script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
|
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<script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
|
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<script src="../../_static/jquery.js"></script>
|
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<script src="../../_static/underscore.js"></script>
|
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<script src="../../_static/_sphinx_javascript_frameworks_compat.js"></script>
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<script src="../../_static/doctools.js"></script>
|
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<script src="../../_static/sphinx_highlight.js"></script>
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<script src="../../_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../search.html" />
|
||||
|
|
@ -82,9 +83,7 @@
|
|||
<span class="kn">from</span> <span class="nn">glob</span> <span class="kn">import</span> <span class="n">glob</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AbstractProtocol">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractProtocol">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">AbstractProtocol</span><span class="p">(</span><span class="n">metaclass</span><span class="o">=</span><span class="n">ABCMeta</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AbstractProtocol"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractProtocol">[docs]</a><span class="k">class</span> <span class="nc">AbstractProtocol</span><span class="p">(</span><span class="n">metaclass</span><span class="o">=</span><span class="n">ABCMeta</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Abstract parent class for sample generation protocols.</span>
|
||||
<span class="sd"> """</span>
|
||||
|
|
@ -99,22 +98,16 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="o">...</span>
|
||||
|
||||
<div class="viewcode-block" id="AbstractProtocol.total">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractProtocol.total">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AbstractProtocol.total"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractProtocol.total">[docs]</a> <span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Indicates the total number of samples that the protocol generates.</span>
|
||||
|
||||
<span class="sd"> :return: The number of samples to generate if known, or `None` otherwise.</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="kc">None</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="kc">None</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="IterateProtocol">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.IterateProtocol">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">IterateProtocol</span><span class="p">(</span><span class="n">AbstractProtocol</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="IterateProtocol"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.IterateProtocol">[docs]</a><span class="k">class</span> <span class="nc">IterateProtocol</span><span class="p">(</span><span class="n">AbstractProtocol</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> A very simple protocol which simply iterates over a list of previously generated samples</span>
|
||||
|
||||
|
|
@ -133,22 +126,16 @@
|
|||
<span class="k">for</span> <span class="n">sample</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">samples</span><span class="p">:</span>
|
||||
<span class="k">yield</span> <span class="n">sample</span><span class="o">.</span><span class="n">Xp</span>
|
||||
|
||||
<div class="viewcode-block" id="IterateProtocol.total">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.IterateProtocol.total">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="IterateProtocol.total"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.IterateProtocol.total">[docs]</a> <span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the number of samples in this protocol</span>
|
||||
|
||||
<span class="sd"> :return: int</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">samples</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">samples</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">AbstractStochasticSeededProtocol</span><span class="p">(</span><span class="n">AbstractProtocol</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol">[docs]</a><span class="k">class</span> <span class="nc">AbstractStochasticSeededProtocol</span><span class="p">(</span><span class="n">AbstractProtocol</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> An `AbstractStochasticSeededProtocol` is a protocol that generates, via any random procedure (e.g.,</span>
|
||||
<span class="sd"> via random sampling), sequences of :class:`quapy.data.base.LabelledCollection` samples.</span>
|
||||
|
|
@ -176,9 +163,7 @@
|
|||
<span class="k">def</span> <span class="nf">random_state</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">random_state</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_random_state</span> <span class="o">=</span> <span class="n">random_state</span>
|
||||
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol.samples_parameters">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol.samples_parameters">[docs]</a>
|
||||
<span class="nd">@abstractmethod</span>
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol.samples_parameters"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol.samples_parameters">[docs]</a> <span class="nd">@abstractmethod</span>
|
||||
<span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> This function has to return all the necessary parameters to replicate the samples</span>
|
||||
|
|
@ -187,10 +172,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="o">...</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol.sample">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol.sample">[docs]</a>
|
||||
<span class="nd">@abstractmethod</span>
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol.sample"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol.sample">[docs]</a> <span class="nd">@abstractmethod</span>
|
||||
<span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">params</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Extract one sample determined by the given parameters</span>
|
||||
|
|
@ -200,7 +182,6 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="o">...</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Yields one sample at a time. The type of object returned depends on the `collator` function. The</span>
|
||||
|
|
@ -218,9 +199,7 @@
|
|||
<span class="k">for</span> <span class="n">params</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">samples_parameters</span><span class="p">():</span>
|
||||
<span class="k">yield</span> <span class="bp">self</span><span class="o">.</span><span class="n">collator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="n">params</span><span class="p">))</span>
|
||||
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol.collator">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol.collator">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">collator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="AbstractStochasticSeededProtocol.collator"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.AbstractStochasticSeededProtocol.collator">[docs]</a> <span class="k">def</span> <span class="nf">collator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> The collator prepares the sample to accommodate the desired output format before returning the output.</span>
|
||||
<span class="sd"> This collator simply returns the sample as it is. Classes inheriting from this abstract class can</span>
|
||||
|
|
@ -230,23 +209,17 @@
|
|||
<span class="sd"> :param args: additional arguments</span>
|
||||
<span class="sd"> :return: the sample adhering to a desired output format (in this case, the sample is returned as it is)</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">sample</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">sample</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">OnLabelledCollectionProtocol</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol">[docs]</a><span class="k">class</span> <span class="nc">OnLabelledCollectionProtocol</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Protocols that generate samples from a :class:`qp.data.LabelledCollection` object.</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="n">RETURN_TYPES</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'sample_prev'</span><span class="p">,</span> <span class="s1">'labelled_collection'</span><span class="p">,</span> <span class="s1">'index'</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol.get_labelled_collection">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol.get_labelled_collection">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_labelled_collection</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol.get_labelled_collection"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol.get_labelled_collection">[docs]</a> <span class="k">def</span> <span class="nf">get_labelled_collection</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the labelled collection on which this protocol acts.</span>
|
||||
|
||||
|
|
@ -254,10 +227,7 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol.on_preclassified_instances">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol.on_preclassified_instances">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">on_preclassified_instances</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pre_classifications</span><span class="p">,</span> <span class="n">in_place</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol.on_preclassified_instances"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol.on_preclassified_instances">[docs]</a> <span class="k">def</span> <span class="nf">on_preclassified_instances</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pre_classifications</span><span class="p">,</span> <span class="n">in_place</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns a copy of this protocol that acts on a modified version of the original</span>
|
||||
<span class="sd"> :class:`qp.data.LabelledCollection` in which the original instances have been replaced</span>
|
||||
|
|
@ -280,10 +250,7 @@
|
|||
<span class="n">new</span> <span class="o">=</span> <span class="n">deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">new</span><span class="o">.</span><span class="n">on_preclassified_instances</span><span class="p">(</span><span class="n">pre_classifications</span><span class="p">,</span> <span class="n">in_place</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol.get_collator">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol.get_collator">[docs]</a>
|
||||
<span class="nd">@classmethod</span>
|
||||
<div class="viewcode-block" id="OnLabelledCollectionProtocol.get_collator"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.OnLabelledCollectionProtocol.get_collator">[docs]</a> <span class="nd">@classmethod</span>
|
||||
<span class="k">def</span> <span class="nf">get_collator</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">return_type</span><span class="o">=</span><span class="s1">'sample_prev'</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns a collator function, i.e., a function that prepares the yielded data</span>
|
||||
|
|
@ -299,14 +266,10 @@
|
|||
<span class="k">if</span> <span class="n">return_type</span><span class="o">==</span><span class="s1">'sample_prev'</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="k">lambda</span> <span class="n">lc</span><span class="p">:</span><span class="n">lc</span><span class="o">.</span><span class="n">Xp</span>
|
||||
<span class="k">elif</span> <span class="n">return_type</span><span class="o">==</span><span class="s1">'labelled_collection'</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="k">lambda</span> <span class="n">lc</span><span class="p">:</span><span class="n">lc</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="k">lambda</span> <span class="n">lc</span><span class="p">:</span><span class="n">lc</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="APP">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">APP</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">,</span> <span class="n">OnLabelledCollectionProtocol</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="APP"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP">[docs]</a><span class="k">class</span> <span class="nc">APP</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">,</span> <span class="n">OnLabelledCollectionProtocol</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Implementation of the artificial prevalence protocol (APP).</span>
|
||||
<span class="sd"> The APP consists of exploring a grid of prevalence values containing `n_prevalences` points (e.g.,</span>
|
||||
|
|
@ -350,9 +313,7 @@
|
|||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">collator</span> <span class="o">=</span> <span class="n">OnLabelledCollectionProtocol</span><span class="o">.</span><span class="n">get_collator</span><span class="p">(</span><span class="n">return_type</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="APP.prevalence_grid">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.prevalence_grid">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">prevalence_grid</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="APP.prevalence_grid"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.prevalence_grid">[docs]</a> <span class="k">def</span> <span class="nf">prevalence_grid</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Generates vectors of prevalence values from an exhaustive grid of prevalence values. The</span>
|
||||
<span class="sd"> number of prevalence values explored for each dimension depends on `n_prevalences`, so that, if, for example,</span>
|
||||
|
|
@ -377,10 +338,7 @@
|
|||
<span class="n">prevs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">repeat</span><span class="p">(</span><span class="n">prevs</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">prevs</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="APP.samples_parameters">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.samples_parameters">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="APP.samples_parameters"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.samples_parameters">[docs]</a> <span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Return all the necessary parameters to replicate the samples as according to the APP protocol.</span>
|
||||
|
||||
|
|
@ -392,10 +350,7 @@
|
|||
<span class="n">indexes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">index</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">indexes</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="APP.sample">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.sample">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="APP.sample"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.sample">[docs]</a> <span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Realizes the sample given the index of the instances.</span>
|
||||
|
||||
|
|
@ -404,23 +359,16 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">sampling_from_index</span><span class="p">(</span><span class="n">index</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="APP.total">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.total">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="APP.total"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.APP.total">[docs]</a> <span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the number of samples that will be generated</span>
|
||||
|
||||
<span class="sd"> :return: int</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">num_prevalence_combinations</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">n_prevalences</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">n_classes</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span><span class="p">)</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">num_prevalence_combinations</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">n_prevalences</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">n_classes</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="NPP">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">NPP</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">,</span> <span class="n">OnLabelledCollectionProtocol</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="NPP"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP">[docs]</a><span class="k">class</span> <span class="nc">NPP</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">,</span> <span class="n">OnLabelledCollectionProtocol</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> A generator of samples that implements the natural prevalence protocol (NPP). The NPP consists of drawing</span>
|
||||
<span class="sd"> samples uniformly at random, therefore approximately preserving the natural prevalence of the collection.</span>
|
||||
|
|
@ -444,9 +392,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span> <span class="o">=</span> <span class="n">random_state</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">collator</span> <span class="o">=</span> <span class="n">OnLabelledCollectionProtocol</span><span class="o">.</span><span class="n">get_collator</span><span class="p">(</span><span class="n">return_type</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="NPP.samples_parameters">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP.samples_parameters">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="NPP.samples_parameters"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP.samples_parameters">[docs]</a> <span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Return all the necessary parameters to replicate the samples as according to the NPP protocol.</span>
|
||||
|
||||
|
|
@ -458,10 +404,7 @@
|
|||
<span class="n">indexes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">index</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">indexes</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="NPP.sample">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP.sample">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="NPP.sample"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP.sample">[docs]</a> <span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Realizes the sample given the index of the instances.</span>
|
||||
|
||||
|
|
@ -470,23 +413,16 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">sampling_from_index</span><span class="p">(</span><span class="n">index</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="NPP.total">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP.total">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="NPP.total"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.NPP.total">[docs]</a> <span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the number of samples that will be generated (equals to "repeats")</span>
|
||||
|
||||
<span class="sd"> :return: int</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="UPP">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">UPP</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">,</span> <span class="n">OnLabelledCollectionProtocol</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="UPP"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP">[docs]</a><span class="k">class</span> <span class="nc">UPP</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">,</span> <span class="n">OnLabelledCollectionProtocol</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> A variant of :class:`APP` that, instead of using a grid of equidistant prevalence values,</span>
|
||||
<span class="sd"> relies on the Kraemer algorithm for sampling unit (k-1)-simplex uniformly at random, with</span>
|
||||
|
|
@ -514,9 +450,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span> <span class="o">=</span> <span class="n">random_state</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">collator</span> <span class="o">=</span> <span class="n">OnLabelledCollectionProtocol</span><span class="o">.</span><span class="n">get_collator</span><span class="p">(</span><span class="n">return_type</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="UPP.samples_parameters">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP.samples_parameters">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="UPP.samples_parameters"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP.samples_parameters">[docs]</a> <span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Return all the necessary parameters to replicate the samples as according to the UPP protocol.</span>
|
||||
|
||||
|
|
@ -528,10 +462,7 @@
|
|||
<span class="n">indexes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">index</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">indexes</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="UPP.sample">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP.sample">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="UPP.sample"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP.sample">[docs]</a> <span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Realizes the sample given the index of the instances.</span>
|
||||
|
||||
|
|
@ -540,23 +471,16 @@
|
|||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">sampling_from_index</span><span class="p">(</span><span class="n">index</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="UPP.total">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP.total">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="UPP.total"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.UPP.total">[docs]</a> <span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the number of samples that will be generated (equals to "repeats")</span>
|
||||
|
||||
<span class="sd"> :return: int</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span></div>
|
||||
</div>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span></div></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DomainMixer">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">DomainMixer</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DomainMixer"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer">[docs]</a><span class="k">class</span> <span class="nc">DomainMixer</span><span class="p">(</span><span class="n">AbstractStochasticSeededProtocol</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Generates mixtures of two domains (A and B) at controlled rates, but preserving the original class prevalence.</span>
|
||||
|
||||
|
|
@ -607,9 +531,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">random_state</span> <span class="o">=</span> <span class="n">random_state</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">collator</span> <span class="o">=</span> <span class="n">OnLabelledCollectionProtocol</span><span class="o">.</span><span class="n">get_collator</span><span class="p">(</span><span class="n">return_type</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="DomainMixer.samples_parameters">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer.samples_parameters">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DomainMixer.samples_parameters"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer.samples_parameters">[docs]</a> <span class="k">def</span> <span class="nf">samples_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Return all the necessary parameters to replicate the samples as according to the this protocol.</span>
|
||||
|
||||
|
|
@ -626,10 +548,7 @@
|
|||
<span class="n">indexesB</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sampleBidx</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">indexesA</span><span class="p">,</span> <span class="n">indexesB</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DomainMixer.sample">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer.sample">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DomainMixer.sample"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer.sample">[docs]</a> <span class="k">def</span> <span class="nf">sample</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Realizes the sample given a pair of indexes of the instances from A and B.</span>
|
||||
|
||||
|
|
@ -641,18 +560,13 @@
|
|||
<span class="n">sampleB</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">B</span><span class="o">.</span><span class="n">sampling_from_index</span><span class="p">(</span><span class="n">indexesB</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">sampleA</span><span class="o">+</span><span class="n">sampleB</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DomainMixer.total">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer.total">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="DomainMixer.total"><a class="viewcode-back" href="../../quapy.html#quapy.protocol.DomainMixer.total">[docs]</a> <span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Returns the number of samples that will be generated (equals to "repeats * mixture_points")</span>
|
||||
|
||||
<span class="sd"> :return: int</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mixture_points</span><span class="p">)</span></div>
|
||||
</div>
|
||||
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">repeats</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mixture_points</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
<span class="c1"># aliases</span>
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="../../">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.util — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="../../_static/css/theme.css" />
|
||||
|
||||
|
||||
<!--[if lt IE 9]>
|
||||
<script src="../../_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
||||
|
||||
<script src="../../_static/jquery.js?v=5d32c60e"></script>
|
||||
<script src="../../_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
||||
<script src="../../_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="../../_static/doctools.js?v=9a2dae69"></script>
|
||||
<script src="../../_static/sphinx_highlight.js?v=dc90522c"></script>
|
||||
<script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
|
||||
<script src="../../_static/jquery.js"></script>
|
||||
<script src="../../_static/underscore.js"></script>
|
||||
<script src="../../_static/_sphinx_javascript_frameworks_compat.js"></script>
|
||||
<script src="../../_static/doctools.js"></script>
|
||||
<script src="../../_static/sphinx_highlight.js"></script>
|
||||
<script src="../../_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../search.html" />
|
||||
|
|
@ -94,9 +95,7 @@
|
|||
<span class="k">return</span> <span class="p">[</span><span class="nb">slice</span><span class="p">(</span><span class="n">job</span> <span class="o">*</span> <span class="n">batch</span><span class="p">,</span> <span class="p">(</span><span class="n">job</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">batch</span> <span class="o">+</span> <span class="p">(</span><span class="n">remainder</span> <span class="k">if</span> <span class="n">job</span> <span class="o">==</span> <span class="n">n_jobs</span> <span class="o">-</span> <span class="mi">1</span> <span class="k">else</span> <span class="mi">0</span><span class="p">))</span> <span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_jobs</span><span class="p">)]</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="map_parallel">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.map_parallel">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">map_parallel</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">n_jobs</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="map_parallel"><a class="viewcode-back" href="../../quapy.html#quapy.util.map_parallel">[docs]</a><span class="k">def</span> <span class="nf">map_parallel</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">n_jobs</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Applies func to n_jobs slices of args. E.g., if args is an array of 99 items and n_jobs=2, then</span>
|
||||
<span class="sd"> func is applied in two parallel processes to args[0:50] and to args[50:99]. func is a function</span>
|
||||
|
|
@ -114,10 +113,7 @@
|
|||
<span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="n">itertools</span><span class="o">.</span><span class="n">chain</span><span class="o">.</span><span class="n">from_iterable</span><span class="p">(</span><span class="n">results</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="parallel">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.parallel">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">parallel</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">n_jobs</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">asarray</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">backend</span><span class="o">=</span><span class="s1">'loky'</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="parallel"><a class="viewcode-back" href="../../quapy.html#quapy.util.parallel">[docs]</a><span class="k">def</span> <span class="nf">parallel</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">n_jobs</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">asarray</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">backend</span><span class="o">=</span><span class="s1">'loky'</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> A wrapper of multiprocessing:</span>
|
||||
|
||||
|
|
@ -151,10 +147,7 @@
|
|||
<span class="k">return</span> <span class="n">out</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="temp_seed">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.temp_seed">[docs]</a>
|
||||
<span class="nd">@contextlib</span><span class="o">.</span><span class="n">contextmanager</span>
|
||||
<div class="viewcode-block" id="temp_seed"><a class="viewcode-back" href="../../quapy.html#quapy.util.temp_seed">[docs]</a><span class="nd">@contextlib</span><span class="o">.</span><span class="n">contextmanager</span>
|
||||
<span class="k">def</span> <span class="nf">temp_seed</span><span class="p">(</span><span class="n">random_state</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Can be used in a "with" context to set a temporal seed without modifying the outer numpy's current state. E.g.:</span>
|
||||
|
|
@ -176,10 +169,7 @@
|
|||
<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">set_state</span><span class="p">(</span><span class="n">state</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="download_file">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.download_file">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">download_file</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">archive_filename</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="download_file"><a class="viewcode-back" href="../../quapy.html#quapy.util.download_file">[docs]</a><span class="k">def</span> <span class="nf">download_file</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">archive_filename</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Downloads a file from a url</span>
|
||||
|
||||
|
|
@ -195,10 +185,7 @@
|
|||
<span class="nb">print</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="download_file_if_not_exists">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.download_file_if_not_exists">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">download_file_if_not_exists</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">archive_filename</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="download_file_if_not_exists"><a class="viewcode-back" href="../../quapy.html#quapy.util.download_file_if_not_exists">[docs]</a><span class="k">def</span> <span class="nf">download_file_if_not_exists</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">archive_filename</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Dowloads a function (using :meth:`download_file`) if the file does not exist.</span>
|
||||
|
||||
|
|
@ -211,10 +198,7 @@
|
|||
<span class="n">download_file</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">archive_filename</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="create_if_not_exist">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.create_if_not_exist">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">create_if_not_exist</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="create_if_not_exist"><a class="viewcode-back" href="../../quapy.html#quapy.util.create_if_not_exist">[docs]</a><span class="k">def</span> <span class="nf">create_if_not_exist</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> An alias to `os.makedirs(path, exist_ok=True)` that also returns the path. This is useful in cases like, e.g.:</span>
|
||||
|
||||
|
|
@ -227,10 +211,7 @@
|
|||
<span class="k">return</span> <span class="n">path</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_quapy_home">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.get_quapy_home">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">get_quapy_home</span><span class="p">():</span>
|
||||
<div class="viewcode-block" id="get_quapy_home"><a class="viewcode-back" href="../../quapy.html#quapy.util.get_quapy_home">[docs]</a><span class="k">def</span> <span class="nf">get_quapy_home</span><span class="p">():</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Gets the home directory of QuaPy, i.e., the directory where QuaPy saves permanent data, such as dowloaded datasets.</span>
|
||||
<span class="sd"> This directory is `~/quapy_data`</span>
|
||||
|
|
@ -242,10 +223,7 @@
|
|||
<span class="k">return</span> <span class="n">home</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="create_parent_dir">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.create_parent_dir">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">create_parent_dir</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="create_parent_dir"><a class="viewcode-back" href="../../quapy.html#quapy.util.create_parent_dir">[docs]</a><span class="k">def</span> <span class="nf">create_parent_dir</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Creates the parent dir (if any) of a given path, if not exists. E.g., for `./path/to/file.txt`, the path `./path/to`</span>
|
||||
<span class="sd"> is created.</span>
|
||||
|
|
@ -257,10 +235,7 @@
|
|||
<span class="n">os</span><span class="o">.</span><span class="n">makedirs</span><span class="p">(</span><span class="n">parentdir</span><span class="p">,</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="save_text_file">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.save_text_file">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">save_text_file</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">text</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="save_text_file"><a class="viewcode-back" href="../../quapy.html#quapy.util.save_text_file">[docs]</a><span class="k">def</span> <span class="nf">save_text_file</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">text</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Saves a text file to disk, given its full path, and creates the parent directory if missing.</span>
|
||||
|
||||
|
|
@ -272,10 +247,7 @@
|
|||
<span class="n">fout</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">text</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="pickled_resource">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.pickled_resource">[docs]</a>
|
||||
<span class="k">def</span> <span class="nf">pickled_resource</span><span class="p">(</span><span class="n">pickle_path</span><span class="p">:</span><span class="nb">str</span><span class="p">,</span> <span class="n">generation_func</span><span class="p">:</span><span class="n">callable</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="pickled_resource"><a class="viewcode-back" href="../../quapy.html#quapy.util.pickled_resource">[docs]</a><span class="k">def</span> <span class="nf">pickled_resource</span><span class="p">(</span><span class="n">pickle_path</span><span class="p">:</span><span class="nb">str</span><span class="p">,</span> <span class="n">generation_func</span><span class="p">:</span><span class="n">callable</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Allows for fast reuse of resources that are generated only once by calling generation_func(\\*args). The next times</span>
|
||||
<span class="sd"> this function is invoked, it loads the pickled resource. Example:</span>
|
||||
|
|
@ -302,7 +274,6 @@
|
|||
<span class="k">return</span> <span class="n">instance</span></div>
|
||||
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_check_sample_size</span><span class="p">(</span><span class="n">sample_size</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">sample_size</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">assert</span> <span class="n">qp</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">'SAMPLE_SIZE'</span><span class="p">]</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">,</span> \
|
||||
|
|
@ -313,9 +284,7 @@
|
|||
<span class="k">return</span> <span class="n">sample_size</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EarlyStop">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.EarlyStop">[docs]</a>
|
||||
<span class="k">class</span> <span class="nc">EarlyStop</span><span class="p">:</span>
|
||||
<div class="viewcode-block" id="EarlyStop"><a class="viewcode-back" href="../../quapy.html#quapy.util.EarlyStop">[docs]</a><span class="k">class</span> <span class="nc">EarlyStop</span><span class="p">:</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> A class implementing the early-stopping condition typically used for training neural networks.</span>
|
||||
|
||||
|
|
@ -370,10 +339,7 @@
|
|||
<span class="bp">self</span><span class="o">.</span><span class="n">STOP</span> <span class="o">=</span> <span class="kc">True</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="timeout">
|
||||
<a class="viewcode-back" href="../../quapy.html#quapy.util.timeout">[docs]</a>
|
||||
<span class="nd">@contextlib</span><span class="o">.</span><span class="n">contextmanager</span>
|
||||
<div class="viewcode-block" id="timeout"><a class="viewcode-back" href="../../quapy.html#quapy.util.timeout">[docs]</a><span class="nd">@contextlib</span><span class="o">.</span><span class="n">contextmanager</span>
|
||||
<span class="k">def</span> <span class="nf">timeout</span><span class="p">(</span><span class="n">seconds</span><span class="p">):</span>
|
||||
<span class="w"> </span><span class="sd">"""</span>
|
||||
<span class="sd"> Opens a context that will launch an exception if not closed after a given number of seconds</span>
|
||||
|
|
@ -404,7 +370,6 @@
|
|||
<span class="k">if</span> <span class="n">seconds</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">signal</span><span class="o">.</span><span class="n">alarm</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,9 +1,20 @@
|
|||
/* Compatability shim for jQuery and underscores.js.
|
||||
/*
|
||||
* _sphinx_javascript_frameworks_compat.js
|
||||
* ~~~~~~~~~~
|
||||
*
|
||||
* Compatability shim for jQuery and underscores.js.
|
||||
*
|
||||
* WILL BE REMOVED IN Sphinx 6.0
|
||||
* xref RemovedInSphinx60Warning
|
||||
*
|
||||
* Copyright Sphinx contributors
|
||||
* Released under the two clause BSD licence
|
||||
*/
|
||||
|
||||
/**
|
||||
* select a different prefix for underscore
|
||||
*/
|
||||
$u = _.noConflict();
|
||||
|
||||
|
||||
/**
|
||||
* small helper function to urldecode strings
|
||||
*
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
*
|
||||
* Sphinx stylesheet -- basic theme.
|
||||
*
|
||||
* :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
|
||||
* :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
|
@ -237,10 +237,6 @@ a.headerlink {
|
|||
visibility: hidden;
|
||||
}
|
||||
|
||||
a:visited {
|
||||
color: #551A8B;
|
||||
}
|
||||
|
||||
h1:hover > a.headerlink,
|
||||
h2:hover > a.headerlink,
|
||||
h3:hover > a.headerlink,
|
||||
|
|
@ -328,7 +324,6 @@ aside.sidebar {
|
|||
p.sidebar-title {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
nav.contents,
|
||||
aside.topic,
|
||||
div.admonition, div.topic, blockquote {
|
||||
|
|
@ -336,7 +331,6 @@ div.admonition, div.topic, blockquote {
|
|||
}
|
||||
|
||||
/* -- topics ---------------------------------------------------------------- */
|
||||
|
||||
nav.contents,
|
||||
aside.topic,
|
||||
div.topic {
|
||||
|
|
@ -612,7 +606,6 @@ ol.simple p,
|
|||
ul.simple p {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
aside.footnote > span,
|
||||
div.citation > span {
|
||||
float: left;
|
||||
|
|
@ -674,16 +667,6 @@ dd {
|
|||
margin-left: 30px;
|
||||
}
|
||||
|
||||
.sig dd {
|
||||
margin-top: 0px;
|
||||
margin-bottom: 0px;
|
||||
}
|
||||
|
||||
.sig dl {
|
||||
margin-top: 0px;
|
||||
margin-bottom: 0px;
|
||||
}
|
||||
|
||||
dl > dd:last-child,
|
||||
dl > dd:last-child > :last-child {
|
||||
margin-bottom: 0;
|
||||
|
|
@ -752,14 +735,6 @@ abbr, acronym {
|
|||
cursor: help;
|
||||
}
|
||||
|
||||
.translated {
|
||||
background-color: rgba(207, 255, 207, 0.2)
|
||||
}
|
||||
|
||||
.untranslated {
|
||||
background-color: rgba(255, 207, 207, 0.2)
|
||||
}
|
||||
|
||||
/* -- code displays --------------------------------------------------------- */
|
||||
|
||||
pre {
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
*
|
||||
* Base JavaScript utilities for all Sphinx HTML documentation.
|
||||
*
|
||||
* :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
|
||||
* :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
const DOCUMENTATION_OPTIONS = {
|
||||
var DOCUMENTATION_OPTIONS = {
|
||||
URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
|
||||
VERSION: '0.1.8',
|
||||
LANGUAGE: 'en',
|
||||
COLLAPSE_INDEX: false,
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@
|
|||
* This script contains the language-specific data used by searchtools.js,
|
||||
* namely the list of stopwords, stemmer, scorer and splitter.
|
||||
*
|
||||
* :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
|
||||
* :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
*
|
||||
* Sphinx JavaScript utilities for the full-text search.
|
||||
*
|
||||
* :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
|
||||
* :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
|
@ -57,12 +57,12 @@ const _removeChildren = (element) => {
|
|||
const _escapeRegExp = (string) =>
|
||||
string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
|
||||
|
||||
const _displayItem = (item, searchTerms, highlightTerms) => {
|
||||
const _displayItem = (item, searchTerms) => {
|
||||
const docBuilder = DOCUMENTATION_OPTIONS.BUILDER;
|
||||
const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT;
|
||||
const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX;
|
||||
const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX;
|
||||
const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY;
|
||||
const contentRoot = document.documentElement.dataset.content_root;
|
||||
|
||||
const [docName, title, anchor, descr, score, _filename] = item;
|
||||
|
||||
|
|
@ -75,24 +75,20 @@ const _displayItem = (item, searchTerms, highlightTerms) => {
|
|||
if (dirname.match(/\/index\/$/))
|
||||
dirname = dirname.substring(0, dirname.length - 6);
|
||||
else if (dirname === "index/") dirname = "";
|
||||
requestUrl = contentRoot + dirname;
|
||||
requestUrl = docUrlRoot + dirname;
|
||||
linkUrl = requestUrl;
|
||||
} else {
|
||||
// normal html builders
|
||||
requestUrl = contentRoot + docName + docFileSuffix;
|
||||
requestUrl = docUrlRoot + docName + docFileSuffix;
|
||||
linkUrl = docName + docLinkSuffix;
|
||||
}
|
||||
let linkEl = listItem.appendChild(document.createElement("a"));
|
||||
linkEl.href = linkUrl + anchor;
|
||||
linkEl.dataset.score = score;
|
||||
linkEl.innerHTML = title;
|
||||
if (descr) {
|
||||
if (descr)
|
||||
listItem.appendChild(document.createElement("span")).innerHTML =
|
||||
" (" + descr + ")";
|
||||
// highlight search terms in the description
|
||||
if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js
|
||||
highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
|
||||
}
|
||||
else if (showSearchSummary)
|
||||
fetch(requestUrl)
|
||||
.then((responseData) => responseData.text())
|
||||
|
|
@ -101,9 +97,6 @@ const _displayItem = (item, searchTerms, highlightTerms) => {
|
|||
listItem.appendChild(
|
||||
Search.makeSearchSummary(data, searchTerms)
|
||||
);
|
||||
// highlight search terms in the summary
|
||||
if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js
|
||||
highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
|
||||
});
|
||||
Search.output.appendChild(listItem);
|
||||
};
|
||||
|
|
@ -122,15 +115,14 @@ const _finishSearch = (resultCount) => {
|
|||
const _displayNextItem = (
|
||||
results,
|
||||
resultCount,
|
||||
searchTerms,
|
||||
highlightTerms,
|
||||
searchTerms
|
||||
) => {
|
||||
// results left, load the summary and display it
|
||||
// this is intended to be dynamic (don't sub resultsCount)
|
||||
if (results.length) {
|
||||
_displayItem(results.pop(), searchTerms, highlightTerms);
|
||||
_displayItem(results.pop(), searchTerms);
|
||||
setTimeout(
|
||||
() => _displayNextItem(results, resultCount, searchTerms, highlightTerms),
|
||||
() => _displayNextItem(results, resultCount, searchTerms),
|
||||
5
|
||||
);
|
||||
}
|
||||
|
|
@ -164,7 +156,7 @@ const Search = {
|
|||
const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html');
|
||||
htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() });
|
||||
const docContent = htmlElement.querySelector('[role="main"]');
|
||||
if (docContent) return docContent.textContent;
|
||||
if (docContent !== undefined) return docContent.textContent;
|
||||
console.warn(
|
||||
"Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template."
|
||||
);
|
||||
|
|
@ -288,9 +280,9 @@ const Search = {
|
|||
let results = [];
|
||||
_removeChildren(document.getElementById("search-progress"));
|
||||
|
||||
const queryLower = query.toLowerCase().trim();
|
||||
const queryLower = query.toLowerCase();
|
||||
for (const [title, foundTitles] of Object.entries(allTitles)) {
|
||||
if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) {
|
||||
if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) {
|
||||
for (const [file, id] of foundTitles) {
|
||||
let score = Math.round(100 * queryLower.length / title.length)
|
||||
results.push([
|
||||
|
|
@ -368,7 +360,7 @@ const Search = {
|
|||
// console.info("search results:", Search.lastresults);
|
||||
|
||||
// print the results
|
||||
_displayNextItem(results, results.length, searchTerms, highlightTerms);
|
||||
_displayNextItem(results, results.length, searchTerms);
|
||||
},
|
||||
|
||||
/**
|
||||
|
|
|
|||
|
|
@ -29,19 +29,14 @@ const _highlight = (node, addItems, text, className) => {
|
|||
}
|
||||
|
||||
span.appendChild(document.createTextNode(val.substr(pos, text.length)));
|
||||
const rest = document.createTextNode(val.substr(pos + text.length));
|
||||
parent.insertBefore(
|
||||
span,
|
||||
parent.insertBefore(
|
||||
rest,
|
||||
document.createTextNode(val.substr(pos + text.length)),
|
||||
node.nextSibling
|
||||
)
|
||||
);
|
||||
node.nodeValue = val.substr(0, pos);
|
||||
/* There may be more occurrences of search term in this node. So call this
|
||||
* function recursively on the remaining fragment.
|
||||
*/
|
||||
_highlight(rest, addItems, text, className);
|
||||
|
||||
if (isInSVG) {
|
||||
const rect = document.createElementNS(
|
||||
|
|
@ -145,10 +140,5 @@ const SphinxHighlight = {
|
|||
},
|
||||
};
|
||||
|
||||
_ready(() => {
|
||||
/* Do not call highlightSearchWords() when we are on the search page.
|
||||
* It will highlight words from the *previous* search query.
|
||||
*/
|
||||
if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords();
|
||||
SphinxHighlight.initEscapeListener();
|
||||
});
|
||||
_ready(SphinxHighlight.highlightSearchWords);
|
||||
_ready(SphinxHighlight.initEscapeListener);
|
||||
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|
|||
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|
@ -1,22 +1,23 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="./">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Index — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css" />
|
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|
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|
||||
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|
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<script src="_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
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|
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<script src="_static/jquery.js?v=5d32c60e"></script>
|
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<script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
||||
<script src="_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="_static/doctools.js?v=9a2dae69"></script>
|
||||
<script src="_static/sphinx_highlight.js?v=dc90522c"></script>
|
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<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
|
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<script src="_static/jquery.js"></script>
|
||||
<script src="_static/underscore.js"></script>
|
||||
<script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
|
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<script src="_static/doctools.js"></script>
|
||||
<script src="_static/sphinx_highlight.js"></script>
|
||||
<script src="_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="#" />
|
||||
<link rel="search" title="Search" href="search.html" />
|
||||
|
|
@ -686,7 +687,7 @@
|
|||
module
|
||||
|
||||
<ul>
|
||||
<li><a href="generated/quapy.html#module-quapy">quapy</a>, <a href="quapy.html#module-quapy">[1]</a>
|
||||
<li><a href="quapy.html#module-quapy">quapy</a>
|
||||
</li>
|
||||
<li><a href="quapy.classification.html#module-quapy.classification">quapy.classification</a>
|
||||
</li>
|
||||
|
|
@ -919,7 +920,7 @@
|
|||
quapy
|
||||
|
||||
<ul>
|
||||
<li><a href="generated/quapy.html#module-quapy">module</a>, <a href="quapy.html#module-quapy">[1]</a>
|
||||
<li><a href="quapy.html#module-quapy">module</a>
|
||||
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|
||||
</ul></li>
|
||||
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|
||||
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|
@ -1261,6 +1262,16 @@
|
|||
<td style="width: 33%; vertical-align: top;"><ul>
|
||||
<li><a href="quapy.data.html#quapy.data.base.Dataset.train_test">train_test (quapy.data.base.Dataset property)</a>
|
||||
</li>
|
||||
<li><a href="quapy.classification.html#quapy.classification.neural.CNNnet.training">training (quapy.classification.neural.CNNnet attribute)</a>
|
||||
|
||||
<ul>
|
||||
<li><a href="quapy.classification.html#quapy.classification.neural.LSTMnet.training">(quapy.classification.neural.LSTMnet attribute)</a>
|
||||
</li>
|
||||
<li><a href="quapy.classification.html#quapy.classification.neural.TextClassifierNet.training">(quapy.classification.neural.TextClassifierNet attribute)</a>
|
||||
</li>
|
||||
<li><a href="quapy.method.html#quapy.method._neural.QuaNetModule.training">(quapy.method._neural.QuaNetModule attribute)</a>
|
||||
</li>
|
||||
</ul></li>
|
||||
<li><a href="quapy.classification.html#quapy.classification.methods.LowRankLogisticRegression.transform">transform() (quapy.classification.methods.LowRankLogisticRegression method)</a>
|
||||
|
||||
<ul>
|
||||
|
|
|
|||
|
|
@ -1,24 +1,24 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="./">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
|
||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Welcome to QuaPy’s documentation! — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css" />
|
||||
|
||||
|
||||
<!--[if lt IE 9]>
|
||||
<script src="_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
||||
|
||||
<script src="_static/jquery.js?v=5d32c60e"></script>
|
||||
<script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
||||
<script src="_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="_static/doctools.js?v=9a2dae69"></script>
|
||||
<script src="_static/sphinx_highlight.js?v=dc90522c"></script>
|
||||
<script async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
|
||||
<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
|
||||
<script src="_static/jquery.js"></script>
|
||||
<script src="_static/underscore.js"></script>
|
||||
<script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
|
||||
<script src="_static/doctools.js"></script>
|
||||
<script src="_static/sphinx_highlight.js"></script>
|
||||
<script src="_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="genindex.html" />
|
||||
<link rel="search" title="Search" href="search.html" />
|
||||
|
|
@ -73,21 +73,21 @@
|
|||
<div itemprop="articleBody">
|
||||
|
||||
<section id="welcome-to-quapy-s-documentation">
|
||||
<h1>Welcome to QuaPy’s documentation!<a class="headerlink" href="#welcome-to-quapy-s-documentation" title="Link to this heading"></a></h1>
|
||||
<h1>Welcome to QuaPy’s documentation!<a class="headerlink" href="#welcome-to-quapy-s-documentation" title="Permalink to this heading"></a></h1>
|
||||
<p>QuaPy is a Python-based open-source framework for quantification.</p>
|
||||
<p>This document contains the API of the modules included in QuaPy.</p>
|
||||
<section id="installation">
|
||||
<h2>Installation<a class="headerlink" href="#installation" title="Link to this heading"></a></h2>
|
||||
<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this heading"></a></h2>
|
||||
<p><cite>pip install quapy</cite></p>
|
||||
</section>
|
||||
<section id="github">
|
||||
<h2>GitHub<a class="headerlink" href="#github" title="Link to this heading"></a></h2>
|
||||
<h2>GitHub<a class="headerlink" href="#github" title="Permalink to this heading"></a></h2>
|
||||
<p>QuaPy is hosted in GitHub at <a class="reference external" href="https://github.com/HLT-ISTI/QuaPy">https://github.com/HLT-ISTI/QuaPy</a></p>
|
||||
<div class="toctree-wrapper compound">
|
||||
</div>
|
||||
</section>
|
||||
<section id="contents">
|
||||
<h2>Contents<a class="headerlink" href="#contents" title="Link to this heading"></a></h2>
|
||||
<h2>Contents<a class="headerlink" href="#contents" title="Permalink to this heading"></a></h2>
|
||||
<div class="toctree-wrapper compound">
|
||||
<ul>
|
||||
<li class="toctree-l1"><a class="reference internal" href="modules.html">quapy</a><ul>
|
||||
|
|
@ -128,12 +128,14 @@
|
|||
<li class="toctree-l6"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.CNNnet"><code class="docutils literal notranslate"><span class="pre">CNNnet</span></code></a><ul>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.CNNnet.document_embedding"><code class="docutils literal notranslate"><span class="pre">CNNnet.document_embedding()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.CNNnet.get_params"><code class="docutils literal notranslate"><span class="pre">CNNnet.get_params()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.CNNnet.training"><code class="docutils literal notranslate"><span class="pre">CNNnet.training</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.CNNnet.vocabulary_size"><code class="docutils literal notranslate"><span class="pre">CNNnet.vocabulary_size</span></code></a></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="toctree-l6"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.LSTMnet"><code class="docutils literal notranslate"><span class="pre">LSTMnet</span></code></a><ul>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.LSTMnet.document_embedding"><code class="docutils literal notranslate"><span class="pre">LSTMnet.document_embedding()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.LSTMnet.get_params"><code class="docutils literal notranslate"><span class="pre">LSTMnet.get_params()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.LSTMnet.training"><code class="docutils literal notranslate"><span class="pre">LSTMnet.training</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.LSTMnet.vocabulary_size"><code class="docutils literal notranslate"><span class="pre">LSTMnet.vocabulary_size</span></code></a></li>
|
||||
</ul>
|
||||
</li>
|
||||
|
|
@ -154,6 +156,7 @@
|
|||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.TextClassifierNet.forward"><code class="docutils literal notranslate"><span class="pre">TextClassifierNet.forward()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.TextClassifierNet.get_params"><code class="docutils literal notranslate"><span class="pre">TextClassifierNet.get_params()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.TextClassifierNet.predict_proba"><code class="docutils literal notranslate"><span class="pre">TextClassifierNet.predict_proba()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.TextClassifierNet.training"><code class="docutils literal notranslate"><span class="pre">TextClassifierNet.training</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.TextClassifierNet.vocabulary_size"><code class="docutils literal notranslate"><span class="pre">TextClassifierNet.vocabulary_size</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.classification.html#quapy.classification.neural.TextClassifierNet.xavier_uniform"><code class="docutils literal notranslate"><span class="pre">TextClassifierNet.xavier_uniform()</span></code></a></li>
|
||||
</ul>
|
||||
|
|
@ -385,6 +388,7 @@
|
|||
<li class="toctree-l6"><a class="reference internal" href="quapy.method.html#quapy.method._neural.QuaNetModule"><code class="docutils literal notranslate"><span class="pre">QuaNetModule</span></code></a><ul>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.method.html#quapy.method._neural.QuaNetModule.device"><code class="docutils literal notranslate"><span class="pre">QuaNetModule.device</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.method.html#quapy.method._neural.QuaNetModule.forward"><code class="docutils literal notranslate"><span class="pre">QuaNetModule.forward()</span></code></a></li>
|
||||
<li class="toctree-l7"><a class="reference internal" href="quapy.method.html#quapy.method._neural.QuaNetModule.training"><code class="docutils literal notranslate"><span class="pre">QuaNetModule.training</span></code></a></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li class="toctree-l6"><a class="reference internal" href="quapy.method.html#quapy.method._neural.QuaNetTrainer"><code class="docutils literal notranslate"><span class="pre">QuaNetTrainer</span></code></a><ul>
|
||||
|
|
@ -673,7 +677,7 @@
|
|||
</section>
|
||||
</section>
|
||||
<section id="indices-and-tables">
|
||||
<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Link to this heading"></a></h1>
|
||||
<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Permalink to this heading"></a></h1>
|
||||
<ul class="simple">
|
||||
<li><p><a class="reference internal" href="genindex.html"><span class="std std-ref">Index</span></a></p></li>
|
||||
<li><p><a class="reference internal" href="py-modindex.html"><span class="std std-ref">Module Index</span></a></p></li>
|
||||
|
|
|
|||
|
|
@ -1,24 +1,24 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="./">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
|
||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
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<title>quapy — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=92fd9be5" />
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<link rel="stylesheet" type="text/css" href="_static/css/theme.css?v=19f00094" />
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<link rel="stylesheet" type="text/css" href="_static/pygments.css" />
|
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<link rel="stylesheet" type="text/css" href="_static/css/theme.css" />
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|
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|
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<script src="_static/js/html5shiv.min.js"></script>
|
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<![endif]-->
|
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|
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<script src="_static/jquery.js?v=5d32c60e"></script>
|
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<script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
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<script src="_static/documentation_options.js?v=22607128"></script>
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<script src="_static/doctools.js?v=9a2dae69"></script>
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<script src="_static/sphinx_highlight.js?v=dc90522c"></script>
|
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<script async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
|
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<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
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<script src="_static/jquery.js"></script>
|
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|
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<script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
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|
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<script src="_static/sphinx_highlight.js"></script>
|
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<script src="_static/js/theme.js"></script>
|
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<link rel="index" title="Index" href="genindex.html" />
|
||||
<link rel="search" title="Search" href="search.html" />
|
||||
|
|
@ -77,7 +77,7 @@
|
|||
<div itemprop="articleBody">
|
||||
|
||||
<section id="quapy">
|
||||
<h1>quapy<a class="headerlink" href="#quapy" title="Link to this heading"></a></h1>
|
||||
<h1>quapy<a class="headerlink" href="#quapy" title="Permalink to this heading"></a></h1>
|
||||
<div class="toctree-wrapper compound">
|
||||
<ul>
|
||||
<li class="toctree-l1"><a class="reference internal" href="quapy.html">quapy package</a><ul>
|
||||
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|
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|
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|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
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<title>Python Module Index — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
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<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=92fd9be5" />
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|
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<script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
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<script src="_static/documentation_options.js?v=22607128"></script>
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<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
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<script src="_static/jquery.js"></script>
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<script src="_static/sphinx_highlight.js"></script>
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<script src="_static/js/theme.js"></script>
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<link rel="index" title="Index" href="genindex.html" />
|
||||
<link rel="search" title="Search" href="search.html" />
|
||||
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|
|
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|
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@ -1,23 +1,24 @@
|
|||
<!DOCTYPE html>
|
||||
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|
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|
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>quapy.classification package — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
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<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=92fd9be5" />
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<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
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<script src="_static/jquery.js"></script>
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<script src="_static/underscore.js"></script>
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<script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
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<script src="_static/sphinx_highlight.js"></script>
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<script src="_static/js/theme.js"></script>
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<link rel="index" title="Index" href="genindex.html" />
|
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<link rel="search" title="Search" href="search.html" />
|
||||
|
|
@ -95,15 +96,15 @@
|
|||
<div itemprop="articleBody">
|
||||
|
||||
<section id="quapy-classification-package">
|
||||
<h1>quapy.classification package<a class="headerlink" href="#quapy-classification-package" title="Link to this heading"></a></h1>
|
||||
<h1>quapy.classification package<a class="headerlink" href="#quapy-classification-package" title="Permalink to this heading"></a></h1>
|
||||
<section id="submodules">
|
||||
<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading"></a></h2>
|
||||
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading"></a></h2>
|
||||
</section>
|
||||
<section id="module-quapy.classification.calibration">
|
||||
<span id="quapy-classification-calibration-module"></span><h2>quapy.classification.calibration module<a class="headerlink" href="#module-quapy.classification.calibration" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-classification-calibration-module"></span><h2>quapy.classification.calibration module<a class="headerlink" href="#module-quapy.classification.calibration" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.BCTSCalibration">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">BCTSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#BCTSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.BCTSCalibration" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">BCTSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#BCTSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.BCTSCalibration" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <a class="reference internal" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase" title="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">RecalibratedProbabilisticClassifierBase</span></code></a></p>
|
||||
<p>Applies the Bias-Corrected Temperature Scaling (BCTS) calibration method from <cite>abstention.calibration</cite>, as defined in
|
||||
<a class="reference external" href="http://proceedings.mlr.press/v119/alexandari20a.html">Alexandari et al. paper</a>:</p>
|
||||
|
|
@ -124,7 +125,7 @@ training set afterwards. Default value is 5.</p></li>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.NBVSCalibration">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">NBVSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#NBVSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.NBVSCalibration" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">NBVSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#NBVSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.NBVSCalibration" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <a class="reference internal" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase" title="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">RecalibratedProbabilisticClassifierBase</span></code></a></p>
|
||||
<p>Applies the No-Bias Vector Scaling (NBVS) calibration method from <cite>abstention.calibration</cite>, as defined in
|
||||
<a class="reference external" href="http://proceedings.mlr.press/v119/alexandari20a.html">Alexandari et al. paper</a>:</p>
|
||||
|
|
@ -145,7 +146,7 @@ training set afterwards. Default value is 5.</p></li>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifier">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">RecalibratedProbabilisticClassifier</span></span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifier"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifier" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">RecalibratedProbabilisticClassifier</span></span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifier"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifier" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
|
||||
<p>Abstract class for (re)calibration method from <cite>abstention.calibration</cite>, as defined in
|
||||
<a class="reference external" href="http://proceedings.mlr.press/v119/alexandari20a.html">Alexandari, A., Kundaje, A., & Shrikumar, A. (2020, November). Maximum likelihood with bias-corrected calibration
|
||||
|
|
@ -154,7 +155,7 @@ is hard-to-beat at label shift adaptation. In International Conference on Machin
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">RecalibratedProbabilisticClassifierBase</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">calibrator</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">RecalibratedProbabilisticClassifierBase</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">calibrator</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">BaseEstimator</span></code>, <a class="reference internal" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifier" title="quapy.classification.calibration.RecalibratedProbabilisticClassifier"><code class="xref py py-class docutils literal notranslate"><span class="pre">RecalibratedProbabilisticClassifier</span></code></a></p>
|
||||
<p>Applies a (re)calibration method from <cite>abstention.calibration</cite>, as defined in
|
||||
<a class="reference external" href="http://proceedings.mlr.press/v119/alexandari20a.html">Alexandari et al. paper</a>.</p>
|
||||
|
|
@ -174,7 +175,7 @@ training set afterwards. Default value is 5.</p></li>
|
|||
</dl>
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.classes_">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">classes_</span></span><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.classes_" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">classes_</span></span><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.classes_" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns the classes on which the classifier has been trained on</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -185,7 +186,7 @@ training set afterwards. Default value is 5.</p></li>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit">
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Fits the calibration for the probabilistic classifier.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -202,7 +203,7 @@ training set afterwards. Default value is 5.</p></li>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_cv">
|
||||
<span class="sig-name descname"><span class="pre">fit_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.fit_cv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_cv" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.fit_cv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_cv" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Fits the calibration in a cross-validation manner, i.e., it generates posterior probabilities for all
|
||||
training instances via cross-validation, and then retrains the classifier on all training instances.
|
||||
The posterior probabilities thus generated are used for calibrating the outputs of the classifier.</p>
|
||||
|
|
@ -221,7 +222,7 @@ The posterior probabilities thus generated are used for calibrating the outputs
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_tr_val">
|
||||
<span class="sig-name descname"><span class="pre">fit_tr_val</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.fit_tr_val"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_tr_val" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit_tr_val</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.fit_tr_val"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.fit_tr_val" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Fits the calibration in a train/val-split manner, i.e.t, it partitions the training instances into a
|
||||
training and a validation set, and then uses the training samples to learn classifier which is then used
|
||||
to generate posterior probabilities for the held-out validation data. These posteriors are used to calibrate
|
||||
|
|
@ -241,7 +242,7 @@ the classifier. The classifier is not retrained on the whole dataset.</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict">
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Predicts class labels for the data instances in <cite>X</cite></p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -255,7 +256,7 @@ the classifier. The classifier is not retrained on the whole dataset.</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict_proba">
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict_proba" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#RecalibratedProbabilisticClassifierBase.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase.predict_proba" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Generates posterior probabilities for the data instances in <cite>X</cite></p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -271,7 +272,7 @@ the classifier. The classifier is not retrained on the whole dataset.</p>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.TSCalibration">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">TSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#TSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.TSCalibration" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">TSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#TSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.TSCalibration" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <a class="reference internal" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase" title="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">RecalibratedProbabilisticClassifierBase</span></code></a></p>
|
||||
<p>Applies the Temperature Scaling (TS) calibration method from <cite>abstention.calibration</cite>, as defined in
|
||||
<a class="reference external" href="http://proceedings.mlr.press/v119/alexandari20a.html">Alexandari et al. paper</a>:</p>
|
||||
|
|
@ -292,7 +293,7 @@ training set afterwards. Default value is 5.</p></li>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.calibration.VSCalibration">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">VSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#VSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.VSCalibration" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.calibration.</span></span><span class="sig-name descname"><span class="pre">VSCalibration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">classifier</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/calibration.html#VSCalibration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.calibration.VSCalibration" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <a class="reference internal" href="#quapy.classification.calibration.RecalibratedProbabilisticClassifierBase" title="quapy.classification.calibration.RecalibratedProbabilisticClassifierBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">RecalibratedProbabilisticClassifierBase</span></code></a></p>
|
||||
<p>Applies the Vector Scaling (VS) calibration method from <cite>abstention.calibration</cite>, as defined in
|
||||
<a class="reference external" href="http://proceedings.mlr.press/v119/alexandari20a.html">Alexandari et al. paper</a>:</p>
|
||||
|
|
@ -313,10 +314,10 @@ training set afterwards. Default value is 5.</p></li>
|
|||
|
||||
</section>
|
||||
<section id="module-quapy.classification.methods">
|
||||
<span id="quapy-classification-methods-module"></span><h2>quapy.classification.methods module<a class="headerlink" href="#module-quapy.classification.methods" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-classification-methods-module"></span><h2>quapy.classification.methods module<a class="headerlink" href="#module-quapy.classification.methods" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.methods.LowRankLogisticRegression">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.methods.</span></span><span class="sig-name descname"><span class="pre">LowRankLogisticRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.methods.</span></span><span class="sig-name descname"><span class="pre">LowRankLogisticRegression</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_components</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">BaseEstimator</span></code></p>
|
||||
<p>An example of a classification method (i.e., an object that implements <cite>fit</cite>, <cite>predict</cite>, and <cite>predict_proba</cite>)
|
||||
that also generates embedded inputs (i.e., that implements <cite>transform</cite>), as those required for
|
||||
|
|
@ -335,7 +336,7 @@ while classification is performed using <code class="xref py py-class docutils l
|
|||
</dl>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.methods.LowRankLogisticRegression.fit">
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.fit" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.fit" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Fit the model according to the given training data. The fit consists of
|
||||
fitting <cite>TruncatedSVD</cite> and then <cite>LogisticRegression</cite> on the low-rank representation.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -353,7 +354,7 @@ fitting <cite>TruncatedSVD</cite> and then <cite>LogisticRegression</cite> on th
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.methods.LowRankLogisticRegression.get_params">
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.get_params" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.get_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Get hyper-parameters for this estimator.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -364,7 +365,7 @@ fitting <cite>TruncatedSVD</cite> and then <cite>LogisticRegression</cite> on th
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.methods.LowRankLogisticRegression.predict">
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.predict" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.predict" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Predicts labels for the instances <cite>X</cite> embedded into the low-rank space.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -379,7 +380,7 @@ instances in <cite>X</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.methods.LowRankLogisticRegression.predict_proba">
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.predict_proba" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.predict_proba" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Predicts posterior probabilities for the instances <cite>X</cite> embedded into the low-rank space.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -393,7 +394,7 @@ instances in <cite>X</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.methods.LowRankLogisticRegression.set_params">
|
||||
<span class="sig-name descname"><span class="pre">set_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">params</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.set_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.set_params" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">set_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">params</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.set_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.set_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Set the parameters of this estimator.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -406,7 +407,7 @@ and eventually also <cite>n_components</cite> for <cite>TruncatedSVD</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.methods.LowRankLogisticRegression.transform">
|
||||
<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.transform" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/methods.html#LowRankLogisticRegression.transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.methods.LowRankLogisticRegression.transform" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns the low-rank approximation of <cite>X</cite> with <cite>n_components</cite> dimensions, or <cite>X</cite> unaltered if
|
||||
<cite>n_components</cite> >= <cite>X.shape[1]</cite>.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -423,10 +424,10 @@ and eventually also <cite>n_components</cite> for <cite>TruncatedSVD</cite></p>
|
|||
|
||||
</section>
|
||||
<section id="module-quapy.classification.neural">
|
||||
<span id="quapy-classification-neural-module"></span><h2>quapy.classification.neural module<a class="headerlink" href="#module-quapy.classification.neural" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-classification-neural-module"></span><h2>quapy.classification.neural module<a class="headerlink" href="#module-quapy.classification.neural" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.CNNnet">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">CNNnet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">vocabulary_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_classes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">embedding_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">repr_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kernel_heights</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[3,</span> <span class="pre">5,</span> <span class="pre">7]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">padding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#CNNnet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.CNNnet" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">CNNnet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">vocabulary_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_classes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">embedding_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">repr_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kernel_heights</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[3,</span> <span class="pre">5,</span> <span class="pre">7]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stride</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">padding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#CNNnet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.CNNnet" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <a class="reference internal" href="#quapy.classification.neural.TextClassifierNet" title="quapy.classification.neural.TextClassifierNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">TextClassifierNet</span></code></a></p>
|
||||
<p>An implementation of <a class="reference internal" href="#quapy.classification.neural.TextClassifierNet" title="quapy.classification.neural.TextClassifierNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.classification.neural.TextClassifierNet</span></code></a> based on
|
||||
Convolutional Neural Networks.</p>
|
||||
|
|
@ -448,7 +449,7 @@ consecutive tokens that each kernel covers</p></li>
|
|||
</dl>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.CNNnet.document_embedding">
|
||||
<span class="sig-name descname"><span class="pre">document_embedding</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#CNNnet.document_embedding"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.CNNnet.document_embedding" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">document_embedding</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#CNNnet.document_embedding"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.CNNnet.document_embedding" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Embeds documents (i.e., performs the forward pass up to the
|
||||
next-to-last layer).</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -466,7 +467,7 @@ dimensionality of the embedding</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.CNNnet.get_params">
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#CNNnet.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.CNNnet.get_params" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#CNNnet.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.CNNnet.get_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Get hyper-parameters for this estimator</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -475,9 +476,14 @@ dimensionality of the embedding</p>
|
|||
</dl>
|
||||
</dd></dl>
|
||||
|
||||
<dl class="py attribute">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.CNNnet.training">
|
||||
<span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">bool</span></em><a class="headerlink" href="#quapy.classification.neural.CNNnet.training" title="Permalink to this definition"></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.CNNnet.vocabulary_size">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.classification.neural.CNNnet.vocabulary_size" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.classification.neural.CNNnet.vocabulary_size" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Return the size of the vocabulary</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -490,7 +496,7 @@ dimensionality of the embedding</p>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.LSTMnet">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">LSTMnet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">vocabulary_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_classes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">embedding_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">repr_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lstm_class_nlayers</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#LSTMnet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.LSTMnet" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">LSTMnet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">vocabulary_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_classes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">embedding_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hidden_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">repr_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lstm_class_nlayers</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">drop_p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#LSTMnet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.LSTMnet" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <a class="reference internal" href="#quapy.classification.neural.TextClassifierNet" title="quapy.classification.neural.TextClassifierNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">TextClassifierNet</span></code></a></p>
|
||||
<p>An implementation of <a class="reference internal" href="#quapy.classification.neural.TextClassifierNet" title="quapy.classification.neural.TextClassifierNet"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.classification.neural.TextClassifierNet</span></code></a> based on
|
||||
Long Short Term Memory networks.</p>
|
||||
|
|
@ -509,7 +515,7 @@ Long Short Term Memory networks.</p>
|
|||
</dl>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.LSTMnet.document_embedding">
|
||||
<span class="sig-name descname"><span class="pre">document_embedding</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#LSTMnet.document_embedding"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.LSTMnet.document_embedding" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">document_embedding</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#LSTMnet.document_embedding"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.LSTMnet.document_embedding" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Embeds documents (i.e., performs the forward pass up to the
|
||||
next-to-last layer).</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -527,7 +533,7 @@ dimensionality of the embedding</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.LSTMnet.get_params">
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#LSTMnet.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.LSTMnet.get_params" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#LSTMnet.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.LSTMnet.get_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Get hyper-parameters for this estimator</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -536,9 +542,14 @@ dimensionality of the embedding</p>
|
|||
</dl>
|
||||
</dd></dl>
|
||||
|
||||
<dl class="py attribute">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.LSTMnet.training">
|
||||
<span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">bool</span></em><a class="headerlink" href="#quapy.classification.neural.LSTMnet.training" title="Permalink to this definition"></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.LSTMnet.vocabulary_size">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.classification.neural.LSTMnet.vocabulary_size" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.classification.neural.LSTMnet.vocabulary_size" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Return the size of the vocabulary</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -551,7 +562,7 @@ dimensionality of the embedding</p>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">NeuralClassifierTrainer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">net</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.classification.neural.TextClassifierNet" title="quapy.classification.neural.TextClassifierNet"><span class="pre">TextClassifierNet</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">lr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weight_decay</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">patience</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size_test</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">512</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">padding_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">300</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'cuda'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">checkpointpath</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'../checkpoint/classifier_net.dat'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">NeuralClassifierTrainer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">net</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.classification.neural.TextClassifierNet" title="quapy.classification.neural.TextClassifierNet"><span class="pre">TextClassifierNet</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">lr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weight_decay</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">patience</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">200</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size_test</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">512</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">padding_length</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">300</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'cuda'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">checkpointpath</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'../checkpoint/classifier_net.dat'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
|
||||
<p>Trains a neural network for text classification.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -574,7 +585,7 @@ according to the evaluation in the held-out validation split (default ‘../chec
|
|||
</dl>
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.device">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">device</span></span><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.device" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">device</span></span><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.device" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Gets the device in which the network is allocated</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -585,7 +596,7 @@ according to the evaluation in the held-out validation split (default ‘../chec
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.fit">
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.fit" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.fit" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Fits the model according to the given training data.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -603,7 +614,7 @@ according to the evaluation in the held-out validation split (default ‘../chec
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.get_params">
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.get_params" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.get_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Get hyper-parameters for this estimator</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -614,7 +625,7 @@ according to the evaluation in the held-out validation split (default ‘../chec
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.predict">
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.predict" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.predict" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Predicts labels for the instances</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -629,7 +640,7 @@ instances in <cite>X</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.predict_proba">
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.predict_proba" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.predict_proba" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Predicts posterior probabilities for the instances</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -643,7 +654,7 @@ instances in <cite>X</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.reset_net_params">
|
||||
<span class="sig-name descname"><span class="pre">reset_net_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">vocab_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_classes</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.reset_net_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.reset_net_params" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">reset_net_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">vocab_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_classes</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.reset_net_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.reset_net_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Reinitialize the network parameters</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -657,7 +668,7 @@ instances in <cite>X</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.set_params">
|
||||
<span class="sig-name descname"><span class="pre">set_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">params</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.set_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.set_params" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">set_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">params</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.set_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.set_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Set the parameters of this trainer and the learner it is training.
|
||||
In this current version, parameter names for the trainer and learner should
|
||||
be disjoint.</p>
|
||||
|
|
@ -670,7 +681,7 @@ be disjoint.</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.NeuralClassifierTrainer.transform">
|
||||
<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.transform" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#NeuralClassifierTrainer.transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.NeuralClassifierTrainer.transform" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns the embeddings of the instances</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -687,12 +698,12 @@ where <cite>embed_size</cite> is defined by the classification network</p>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">TextClassifierNet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">TextClassifierNet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">Module</span></code></p>
|
||||
<p>Abstract Text classifier (<cite>torch.nn.Module</cite>)</p>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.dimensions">
|
||||
<span class="sig-name descname"><span class="pre">dimensions</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.dimensions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.dimensions" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">dimensions</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.dimensions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.dimensions" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Gets the number of dimensions of the embedding space</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -703,7 +714,7 @@ where <cite>embed_size</cite> is defined by the classification network</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.document_embedding">
|
||||
<em class="property"><span class="pre">abstract</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">document_embedding</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.document_embedding"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.document_embedding" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">abstract</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">document_embedding</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.document_embedding"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.document_embedding" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Embeds documents (i.e., performs the forward pass up to the
|
||||
next-to-last layer).</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -721,7 +732,7 @@ dimensionality of the embedding</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.forward">
|
||||
<span class="sig-name descname"><span class="pre">forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.forward"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.forward" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.forward"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.forward" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Performs the forward pass.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -737,7 +748,7 @@ for each of the instances and classes</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.get_params">
|
||||
<em class="property"><span class="pre">abstract</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.get_params" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">abstract</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_params</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.get_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.get_params" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Get hyper-parameters for this estimator</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -748,7 +759,7 @@ for each of the instances and classes</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.predict_proba">
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.predict_proba" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict_proba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.predict_proba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.predict_proba" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Predicts posterior probabilities for the instances in <cite>x</cite></p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -762,9 +773,14 @@ is length of the pad in the batch</p>
|
|||
</dl>
|
||||
</dd></dl>
|
||||
|
||||
<dl class="py attribute">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.training">
|
||||
<span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">bool</span></em><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.training" title="Permalink to this definition"></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.vocabulary_size">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.vocabulary_size" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.vocabulary_size" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Return the size of the vocabulary</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -775,7 +791,7 @@ is length of the pad in the batch</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TextClassifierNet.xavier_uniform">
|
||||
<span class="sig-name descname"><span class="pre">xavier_uniform</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.xavier_uniform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.xavier_uniform" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">xavier_uniform</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TextClassifierNet.xavier_uniform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TextClassifierNet.xavier_uniform" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Performs Xavier initialization of the network parameters</p>
|
||||
</dd></dl>
|
||||
|
||||
|
|
@ -783,7 +799,7 @@ is length of the pad in the batch</p>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TorchDataset">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">TorchDataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TorchDataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TorchDataset" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.neural.</span></span><span class="sig-name descname"><span class="pre">TorchDataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TorchDataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TorchDataset" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">Dataset</span></code></p>
|
||||
<p>Transforms labelled instances into a Torch’s <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.utils.data.DataLoader</span></code> object</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -796,7 +812,7 @@ is length of the pad in the batch</p>
|
|||
</dl>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.neural.TorchDataset.asDataloader">
|
||||
<span class="sig-name descname"><span class="pre">asDataloader</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">batch_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pad_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TorchDataset.asDataloader"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TorchDataset.asDataloader" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">asDataloader</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">batch_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pad_length</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/neural.html#TorchDataset.asDataloader"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.neural.TorchDataset.asDataloader" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Converts the labelled collection into a Torch DataLoader with dynamic padding for
|
||||
the batch</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -820,10 +836,10 @@ applied, meaning that if the longest document in the batch is shorter than
|
|||
|
||||
</section>
|
||||
<section id="module-quapy.classification.svmperf">
|
||||
<span id="quapy-classification-svmperf-module"></span><h2>quapy.classification.svmperf module<a class="headerlink" href="#module-quapy.classification.svmperf" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-classification-svmperf-module"></span><h2>quapy.classification.svmperf module<a class="headerlink" href="#module-quapy.classification.svmperf" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.classification.svmperf.SVMperf">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.svmperf.</span></span><span class="sig-name descname"><span class="pre">SVMperf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">svmperf_base</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">C</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.01</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">host_folder</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.classification.svmperf.</span></span><span class="sig-name descname"><span class="pre">SVMperf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">svmperf_base</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">C</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.01</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'01'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">host_folder</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">BaseEstimator</span></code>, <code class="xref py py-class docutils literal notranslate"><span class="pre">ClassifierMixin</span></code></p>
|
||||
<p>A wrapper for the <a class="reference external" href="https://www.cs.cornell.edu/people/tj/svm_light/svm_perf.html">SVM-perf package</a> by Thorsten Joachims.
|
||||
When using losses for quantification, the source code has to be patched. See
|
||||
|
|
@ -848,7 +864,7 @@ for further details.</p>
|
|||
</dl>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.svmperf.SVMperf.decision_function">
|
||||
<span class="sig-name descname"><span class="pre">decision_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf.decision_function"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.decision_function" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">decision_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf.decision_function"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.decision_function" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Evaluate the decision function for the samples in <cite>X</cite>.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -865,7 +881,7 @@ for further details.</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.svmperf.SVMperf.fit">
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.fit" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.fit" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Trains the SVM for the multivariate performance loss</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -882,7 +898,7 @@ for further details.</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.classification.svmperf.SVMperf.predict">
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.predict" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/classification/svmperf.html#SVMperf.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.predict" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Predicts labels for the instances <cite>X</cite></p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -897,14 +913,14 @@ instances in <cite>X</cite></p>
|
|||
|
||||
<dl class="py attribute">
|
||||
<dt class="sig sig-object py" id="quapy.classification.svmperf.SVMperf.valid_losses">
|
||||
<span class="sig-name descname"><span class="pre">valid_losses</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">{'01':</span> <span class="pre">0,</span> <span class="pre">'f1':</span> <span class="pre">1,</span> <span class="pre">'kld':</span> <span class="pre">12,</span> <span class="pre">'mae':</span> <span class="pre">26,</span> <span class="pre">'mrae':</span> <span class="pre">27,</span> <span class="pre">'nkld':</span> <span class="pre">13,</span> <span class="pre">'q':</span> <span class="pre">22,</span> <span class="pre">'qacc':</span> <span class="pre">23,</span> <span class="pre">'qf1':</span> <span class="pre">24,</span> <span class="pre">'qgm':</span> <span class="pre">25}</span></em><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.valid_losses" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">valid_losses</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">{'01':</span> <span class="pre">0,</span> <span class="pre">'f1':</span> <span class="pre">1,</span> <span class="pre">'kld':</span> <span class="pre">12,</span> <span class="pre">'mae':</span> <span class="pre">26,</span> <span class="pre">'mrae':</span> <span class="pre">27,</span> <span class="pre">'nkld':</span> <span class="pre">13,</span> <span class="pre">'q':</span> <span class="pre">22,</span> <span class="pre">'qacc':</span> <span class="pre">23,</span> <span class="pre">'qf1':</span> <span class="pre">24,</span> <span class="pre">'qgm':</span> <span class="pre">25}</span></em><a class="headerlink" href="#quapy.classification.svmperf.SVMperf.valid_losses" title="Permalink to this definition"></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
</dd></dl>
|
||||
|
||||
</section>
|
||||
<section id="module-quapy.classification">
|
||||
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-quapy.classification" title="Link to this heading"></a></h2>
|
||||
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-quapy.classification" title="Permalink to this heading"></a></h2>
|
||||
</section>
|
||||
</section>
|
||||
|
||||
|
|
|
|||
|
|
@ -1,23 +1,24 @@
|
|||
<!DOCTYPE html>
|
||||
<html class="writer-html5" lang="en" data-content_root="./">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
|
||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>quapy.data package — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css" />
|
||||
|
||||
|
||||
<!--[if lt IE 9]>
|
||||
<script src="_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
||||
|
||||
<script src="_static/jquery.js?v=5d32c60e"></script>
|
||||
<script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
||||
<script src="_static/documentation_options.js?v=22607128"></script>
|
||||
<script src="_static/doctools.js?v=9a2dae69"></script>
|
||||
<script src="_static/sphinx_highlight.js?v=dc90522c"></script>
|
||||
<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
|
||||
<script src="_static/jquery.js"></script>
|
||||
<script src="_static/underscore.js"></script>
|
||||
<script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
|
||||
<script src="_static/doctools.js"></script>
|
||||
<script src="_static/sphinx_highlight.js"></script>
|
||||
<script src="_static/js/theme.js"></script>
|
||||
<link rel="index" title="Index" href="genindex.html" />
|
||||
<link rel="search" title="Search" href="search.html" />
|
||||
|
|
@ -95,15 +96,15 @@
|
|||
<div itemprop="articleBody">
|
||||
|
||||
<section id="quapy-data-package">
|
||||
<h1>quapy.data package<a class="headerlink" href="#quapy-data-package" title="Link to this heading"></a></h1>
|
||||
<h1>quapy.data package<a class="headerlink" href="#quapy-data-package" title="Permalink to this heading"></a></h1>
|
||||
<section id="submodules">
|
||||
<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading"></a></h2>
|
||||
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading"></a></h2>
|
||||
</section>
|
||||
<section id="module-quapy.data.base">
|
||||
<span id="quapy-data-base-module"></span><h2>quapy.data.base module<a class="headerlink" href="#module-quapy.data.base" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-data-base-module"></span><h2>quapy.data.base module<a class="headerlink" href="#module-quapy.data.base" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.data.base.</span></span><span class="sig-name descname"><span class="pre">Dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">training</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">test</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">vocabulary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.data.base.</span></span><span class="sig-name descname"><span class="pre">Dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">training</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">test</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">vocabulary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">dict</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
|
||||
<p>Abstraction of training and test <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> objects.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -118,7 +119,7 @@
|
|||
</dl>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.SplitStratified">
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">SplitStratified</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">collection</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.6</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.SplitStratified"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.SplitStratified" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">SplitStratified</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">collection</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.6</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.SplitStratified"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.SplitStratified" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Generates a <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dataset</span></code></a> from a stratified split of a <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> instance.
|
||||
See <a class="reference internal" href="#quapy.data.base.LabelledCollection.split_stratified" title="quapy.data.base.LabelledCollection.split_stratified"><code class="xref py py-meth docutils literal notranslate"><span class="pre">LabelledCollection.split_stratified()</span></code></a></p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -136,7 +137,7 @@ See <a class="reference internal" href="#quapy.data.base.LabelledCollection.spli
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.binary">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">binary</span></span><a class="headerlink" href="#quapy.data.base.Dataset.binary" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">binary</span></span><a class="headerlink" href="#quapy.data.base.Dataset.binary" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns True if the training collection is labelled according to two classes</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -147,7 +148,7 @@ See <a class="reference internal" href="#quapy.data.base.LabelledCollection.spli
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.classes_">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">classes_</span></span><a class="headerlink" href="#quapy.data.base.Dataset.classes_" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">classes_</span></span><a class="headerlink" href="#quapy.data.base.Dataset.classes_" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>The classes according to which the training collection is labelled</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -158,7 +159,7 @@ See <a class="reference internal" href="#quapy.data.base.LabelledCollection.spli
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.kFCV">
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">kFCV</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">nfolds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nrepeats</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.kFCV"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.kFCV" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">kFCV</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">nfolds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nrepeats</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.kFCV"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.kFCV" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Generator of stratified folds to be used in k-fold cross validation. This function is only a wrapper around
|
||||
<a class="reference internal" href="#quapy.data.base.LabelledCollection.kFCV" title="quapy.data.base.LabelledCollection.kFCV"><code class="xref py py-meth docutils literal notranslate"><span class="pre">LabelledCollection.kFCV()</span></code></a> that returns <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dataset</span></code></a> instances made of training and test folds.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -177,7 +178,7 @@ See <a class="reference internal" href="#quapy.data.base.LabelledCollection.spli
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.load">
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loader_func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">loader_kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.load"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.load" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loader_func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">loader_kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.load"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.load" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a training and a test labelled set of data and convert it into a <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dataset</span></code></a> instance.
|
||||
The function in charge of reading the instances must be specified. This function can be a custom one, or any of
|
||||
the reading functions defined in <a class="reference internal" href="#module-quapy.data.reader" title="quapy.data.reader"><code class="xref py py-mod docutils literal notranslate"><span class="pre">quapy.data.reader</span></code></a> module.</p>
|
||||
|
|
@ -201,7 +202,7 @@ See <a class="reference internal" href="#quapy.data.base.LabelledCollection.load
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.n_classes">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n_classes</span></span><a class="headerlink" href="#quapy.data.base.Dataset.n_classes" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n_classes</span></span><a class="headerlink" href="#quapy.data.base.Dataset.n_classes" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>The number of classes according to which the training collection is labelled</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -212,7 +213,7 @@ See <a class="reference internal" href="#quapy.data.base.LabelledCollection.load
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.reduce">
|
||||
<span class="sig-name descname"><span class="pre">reduce</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_test</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.reduce"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.reduce" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">reduce</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_test</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.reduce"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.reduce" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Reduce the number of instances in place for quick experiments. Preserves the prevalence of each set.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -229,7 +230,7 @@ See <a class="reference internal" href="#quapy.data.base.LabelledCollection.load
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.stats">
|
||||
<span class="sig-name descname"><span class="pre">stats</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">show</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.stats"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.stats" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">stats</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">show</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#Dataset.stats"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.Dataset.stats" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns (and eventually prints) a dictionary with some stats of this dataset. E.g.,:</p>
|
||||
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">data</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">datasets</span><span class="o">.</span><span class="n">fetch_reviews</span><span class="p">(</span><span class="s1">'kindle'</span><span class="p">,</span> <span class="n">tfidf</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">min_df</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
|
||||
<span class="gp">>>> </span><span class="n">data</span><span class="o">.</span><span class="n">stats</span><span class="p">()</span>
|
||||
|
|
@ -252,7 +253,7 @@ the collection), <cite>prevs</cite> (the prevalence values for each class)</p>
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.train_test">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">train_test</span></span><a class="headerlink" href="#quapy.data.base.Dataset.train_test" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">train_test</span></span><a class="headerlink" href="#quapy.data.base.Dataset.train_test" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Alias to <cite>self.training</cite> and <cite>self.test</cite></p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -266,7 +267,7 @@ the collection), <cite>prevs</cite> (the prevalence values for each class)</p>
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.Dataset.vocabulary_size">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.data.base.Dataset.vocabulary_size" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">vocabulary_size</span></span><a class="headerlink" href="#quapy.data.base.Dataset.vocabulary_size" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>If the dataset is textual, and the vocabulary was indicated, returns the size of the vocabulary</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -279,7 +280,7 @@ the collection), <cite>prevs</cite> (the prevalence values for each class)</p>
|
|||
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.data.base.</span></span><span class="sig-name descname"><span class="pre">LabelledCollection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.data.base.</span></span><span class="sig-name descname"><span class="pre">LabelledCollection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
|
||||
<p>A LabelledCollection is a set of objects each with a label attached to each of them.
|
||||
This class implements several sampling routines and other utilities.</p>
|
||||
|
|
@ -296,7 +297,7 @@ from the labels. The classes must be indicated in cases in which some of the lab
|
|||
</dl>
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.X">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">X</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.X" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">X</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.X" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>An alias to self.instances</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -307,7 +308,7 @@ from the labels. The classes must be indicated in cases in which some of the lab
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.Xp">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Xp</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.Xp" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Xp</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.Xp" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Gets the instances and the true prevalence. This is useful when implementing evaluation protocols from
|
||||
a <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> object.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -319,7 +320,7 @@ a <a class="reference internal" href="#quapy.data.base.LabelledCollection" title
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.Xy">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Xy</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.Xy" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Xy</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.Xy" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Gets the instances and labels. This is useful when working with <cite>sklearn</cite> estimators, e.g.:</p>
|
||||
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">svm</span> <span class="o">=</span> <span class="n">LinearSVC</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="o">*</span><span class="n">my_collection</span><span class="o">.</span><span class="n">Xy</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
|
|
@ -333,7 +334,7 @@ a <a class="reference internal" href="#quapy.data.base.LabelledCollection" title
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.binary">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">binary</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.binary" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">binary</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.binary" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns True if the number of classes is 2</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -344,7 +345,7 @@ a <a class="reference internal" href="#quapy.data.base.LabelledCollection" title
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.counts">
|
||||
<span class="sig-name descname"><span class="pre">counts</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.counts"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.counts" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">counts</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.counts"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.counts" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns the number of instances for each of the classes in the codeframe.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -356,7 +357,7 @@ as listed by <cite>self.classes_</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.join">
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">join</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.join"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.join" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">join</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.join"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.join" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns a new <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> as the union of the collections given in input.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -370,7 +371,7 @@ as listed by <cite>self.classes_</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.kFCV">
|
||||
<span class="sig-name descname"><span class="pre">kFCV</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nfolds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nrepeats</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.kFCV"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.kFCV" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">kFCV</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nfolds</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nrepeats</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.kFCV"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.kFCV" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Generator of stratified folds to be used in k-fold cross validation.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -388,7 +389,7 @@ as listed by <cite>self.classes_</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.load">
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loader_func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">loader_kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.load"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.load" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loader_func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">classes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">loader_kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.load"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.load" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a labelled set of data and convert it into a <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> instance. The function in charge
|
||||
of reading the instances must be specified. This function can be a custom one, or any of the reading functions
|
||||
defined in <a class="reference internal" href="#module-quapy.data.reader" title="quapy.data.reader"><code class="xref py py-mod docutils literal notranslate"><span class="pre">quapy.data.reader</span></code></a> module.</p>
|
||||
|
|
@ -411,7 +412,7 @@ these arguments are used to call <cite>loader_func(path, **loader_kwargs)</cite>
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.n_classes">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n_classes</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.n_classes" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">n_classes</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.n_classes" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>The number of classes</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -422,7 +423,7 @@ these arguments are used to call <cite>loader_func(path, **loader_kwargs)</cite>
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.p">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">p</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.p" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">p</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.p" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>An alias to self.prevalence()</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -433,7 +434,7 @@ these arguments are used to call <cite>loader_func(path, **loader_kwargs)</cite>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.prevalence">
|
||||
<span class="sig-name descname"><span class="pre">prevalence</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.prevalence"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.prevalence" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">prevalence</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.prevalence"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.prevalence" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns the prevalence, or relative frequency, of the classes in the codeframe.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -445,7 +446,7 @@ as listed by <cite>self.classes_</cite></p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.sampling">
|
||||
<span class="sig-name descname"><span class="pre">sampling</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">prevs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.sampling"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.sampling" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">sampling</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">prevs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.sampling"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.sampling" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Return a random sample (an instance of <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a>) of desired size and desired prevalence
|
||||
values. For each class, the sampling is drawn without replacement if the requested prevalence is larger than
|
||||
the actual prevalence of the class, or with replacement otherwise.</p>
|
||||
|
|
@ -469,7 +470,7 @@ prevalence == <cite>prevs</cite> if the exact prevalence values can be met as pr
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.sampling_from_index">
|
||||
<span class="sig-name descname"><span class="pre">sampling_from_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">index</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.sampling_from_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.sampling_from_index" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">sampling_from_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">index</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.sampling_from_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.sampling_from_index" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns an instance of <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> whose elements are sampled from this collection using the
|
||||
index.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -484,7 +485,7 @@ index.</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.sampling_index">
|
||||
<span class="sig-name descname"><span class="pre">sampling_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">prevs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.sampling_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.sampling_index" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">sampling_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">prevs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shuffle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.sampling_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.sampling_index" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns an index to be used to extract a random sample of desired size and desired prevalence values. If the
|
||||
prevalence values are not specified, then returns the index of a uniform sampling.
|
||||
For each class, the sampling is drawn with replacement if the requested prevalence is larger than
|
||||
|
|
@ -508,7 +509,7 @@ it is constrained. E.g., for binary collections, only the prevalence <cite>p</ci
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.split_random">
|
||||
<span class="sig-name descname"><span class="pre">split_random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train_prop</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.split_random"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.split_random" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">split_random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train_prop</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.split_random"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.split_random" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns two instances of <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> split randomly from this collection, at desired
|
||||
proportion.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -529,7 +530,7 @@ second one with <cite>1-train_prop</cite> elements</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.split_stratified">
|
||||
<span class="sig-name descname"><span class="pre">split_stratified</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train_prop</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.split_stratified"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.split_stratified" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">split_stratified</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">train_prop</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.split_stratified"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.split_stratified" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns two instances of <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a> split with stratification from this collection, at desired
|
||||
proportion.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -550,7 +551,7 @@ second one with <cite>1-train_prop</cite> elements</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.stats">
|
||||
<span class="sig-name descname"><span class="pre">stats</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">show</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.stats"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.stats" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">stats</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">show</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.stats"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.stats" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns (and eventually prints) a dictionary with some stats of this collection. E.g.,:</p>
|
||||
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">data</span> <span class="o">=</span> <span class="n">qp</span><span class="o">.</span><span class="n">datasets</span><span class="o">.</span><span class="n">fetch_reviews</span><span class="p">(</span><span class="s1">'kindle'</span><span class="p">,</span> <span class="n">tfidf</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">min_df</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
|
||||
<span class="gp">>>> </span><span class="n">data</span><span class="o">.</span><span class="n">training</span><span class="o">.</span><span class="n">stats</span><span class="p">()</span>
|
||||
|
|
@ -572,7 +573,7 @@ values for each class)</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.uniform_sampling">
|
||||
<span class="sig-name descname"><span class="pre">uniform_sampling</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.uniform_sampling"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.uniform_sampling" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">uniform_sampling</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.uniform_sampling"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.uniform_sampling" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns a uniform sample (an instance of <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabelledCollection</span></code></a>) of desired size. The sampling is drawn
|
||||
with replacement if the requested size is greater than the number of instances, or without replacement
|
||||
otherwise.</p>
|
||||
|
|
@ -591,7 +592,7 @@ otherwise.</p>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.uniform_sampling_index">
|
||||
<span class="sig-name descname"><span class="pre">uniform_sampling_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.uniform_sampling_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.uniform_sampling_index" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">uniform_sampling_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">random_state</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/base.html#LabelledCollection.uniform_sampling_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.base.LabelledCollection.uniform_sampling_index" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Returns an index to be used to extract a uniform sample of desired size. The sampling is drawn
|
||||
with replacement if the requested size is greater than the number of instances, or without replacement
|
||||
otherwise.</p>
|
||||
|
|
@ -610,7 +611,7 @@ otherwise.</p>
|
|||
|
||||
<dl class="py property">
|
||||
<dt class="sig sig-object py" id="quapy.data.base.LabelledCollection.y">
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">y</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.y" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">y</span></span><a class="headerlink" href="#quapy.data.base.LabelledCollection.y" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>An alias to self.labels</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -623,10 +624,10 @@ otherwise.</p>
|
|||
|
||||
</section>
|
||||
<section id="module-quapy.data.datasets">
|
||||
<span id="quapy-data-datasets-module"></span><h2>quapy.data.datasets module<a class="headerlink" href="#module-quapy.data.datasets" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-data-datasets-module"></span><h2>quapy.data.datasets module<a class="headerlink" href="#module-quapy.data.datasets" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_IFCB">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_IFCB</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">single_sample_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">for_model_selection</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_IFCB"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_IFCB" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_IFCB</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">single_sample_train</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">for_model_selection</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_IFCB"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_IFCB" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads the IFCB dataset for quantification from <a class="reference external" href="https://zenodo.org/records/10036244">Zenodo</a> (for more
|
||||
information on this dataset, please follow the zenodo link).
|
||||
This dataset is based on the data available publicly at
|
||||
|
|
@ -658,7 +659,7 @@ i.e., a sampling protocol that returns a series of samples labelled by prevalenc
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_UCIBinaryDataset">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIBinaryDataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIBinaryDataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIBinaryDataset" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIBinaryDataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIBinaryDataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIBinaryDataset" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a UCI dataset as an instance of <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.Dataset</span></code></a>, as used in
|
||||
<a class="reference external" href="https://www.sciencedirect.com/science/article/pii/S1566253516300628">Pérez-Gállego, P., Quevedo, J. R., & del Coz, J. J. (2017).
|
||||
Using ensembles for problems with characterizable changes in data distribution: A case study on quantification.
|
||||
|
|
@ -688,7 +689,7 @@ The list of valid dataset names can be accessed in <cite>quapy.data.datasets.UCI
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_UCIBinaryLabelledCollection">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIBinaryLabelledCollection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIBinaryLabelledCollection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIBinaryLabelledCollection" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIBinaryLabelledCollection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIBinaryLabelledCollection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIBinaryLabelledCollection" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a UCI collection as an instance of <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.LabelledCollection</span></code></a>, as used in
|
||||
<a class="reference external" href="https://www.sciencedirect.com/science/article/pii/S1566253516300628">Pérez-Gállego, P., Quevedo, J. R., & del Coz, J. J. (2017).
|
||||
Using ensembles for problems with characterizable changes in data distribution: A case study on quantification.
|
||||
|
|
@ -725,7 +726,7 @@ This can be reproduced by using <a class="reference internal" href="#quapy.data.
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_UCIMulticlassDataset">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIMulticlassDataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIMulticlassDataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIMulticlassDataset" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIMulticlassDataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">test_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIMulticlassDataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIMulticlassDataset" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a UCI multiclass dataset as an instance of <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.Dataset</span></code></a>.</p>
|
||||
<p>The list of available datasets is taken from <a class="reference external" href="https://archive.ics.uci.edu/">https://archive.ics.uci.edu/</a>, following these criteria:
|
||||
- It has more than 1000 instances
|
||||
|
|
@ -758,7 +759,7 @@ This can be reproduced by using <a class="reference internal" href="#quapy.data.
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_UCIMulticlassLabelledCollection">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIMulticlassLabelledCollection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIMulticlassLabelledCollection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIMulticlassLabelledCollection" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_UCIMulticlassLabelledCollection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><span class="pre">LabelledCollection</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_UCIMulticlassLabelledCollection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_UCIMulticlassLabelledCollection" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a UCI multiclass collection as an instance of <a class="reference internal" href="#quapy.data.base.LabelledCollection" title="quapy.data.base.LabelledCollection"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.LabelledCollection</span></code></a>.</p>
|
||||
<p>The list of available datasets is taken from <a class="reference external" href="https://archive.ics.uci.edu/">https://archive.ics.uci.edu/</a>, following these criteria:
|
||||
- It has more than 1000 instances
|
||||
|
|
@ -791,7 +792,7 @@ This can be reproduced by using <a class="reference internal" href="#quapy.data.
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_lequa2022">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_lequa2022</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_lequa2022"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_lequa2022" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_lequa2022</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">task</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_lequa2022"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_lequa2022" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads the official datasets provided for the <a class="reference external" href="https://lequa2022.github.io/index">LeQua</a> competition.
|
||||
In brief, there are 4 tasks (T1A, T1B, T2A, T2B) having to do with text quantification
|
||||
problems. Tasks T1A and T1B provide documents in vector form, while T2A and T2B provide raw documents instead.
|
||||
|
|
@ -822,7 +823,7 @@ that return a series of samples stored in a directory which are labelled by prev
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_reviews">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_reviews</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tfidf</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pickle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_reviews"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_reviews" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_reviews</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tfidf</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pickle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_reviews"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_reviews" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a Reviews dataset as a Dataset instance, as used in
|
||||
<a class="reference external" href="https://dl.acm.org/doi/abs/10.1145/3269206.3269287">Esuli, A., Moreo, A., and Sebastiani, F. “A recurrent neural network for sentiment quantification.”
|
||||
Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 2018.</a>.
|
||||
|
|
@ -848,7 +849,7 @@ faster subsequent invokations</p></li>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.fetch_twitter">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_twitter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">for_model_selection</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pickle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_twitter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_twitter" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">fetch_twitter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset_name</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">for_model_selection</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_home</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pickle</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></span><a class="reference internal" href="_modules/quapy/data/datasets.html#fetch_twitter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.fetch_twitter" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Loads a Twitter dataset as a <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.Dataset</span></code></a> instance, as used in:
|
||||
<a class="reference external" href="https://link.springer.com/content/pdf/10.1007/s13278-016-0327-z.pdf">Gao, W., Sebastiani, F.: From classification to quantification in tweet sentiment analysis.
|
||||
Social Network Analysis and Mining6(19), 1–22 (2016)</a>
|
||||
|
|
@ -879,15 +880,15 @@ faster subsequent invokations</p></li>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.datasets.warn">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">warn</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/datasets.html#warn"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.warn" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.datasets.</span></span><span class="sig-name descname"><span class="pre">warn</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/datasets.html#warn"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.datasets.warn" title="Permalink to this definition"></a></dt>
|
||||
<dd></dd></dl>
|
||||
|
||||
</section>
|
||||
<section id="module-quapy.data.preprocessing">
|
||||
<span id="quapy-data-preprocessing-module"></span><h2>quapy.data.preprocessing module<a class="headerlink" href="#module-quapy.data.preprocessing" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-data-preprocessing-module"></span><h2>quapy.data.preprocessing module<a class="headerlink" href="#module-quapy.data.preprocessing" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py class">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.IndexTransformer">
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">IndexTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer" title="Link to this definition"></a></dt>
|
||||
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">IndexTransformer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
|
||||
<p>This class implements a sklearn’s-style transformer that indexes text as numerical ids for the tokens it
|
||||
contains, and that would be generated by sklearn’s
|
||||
|
|
@ -901,7 +902,7 @@ contains, and that would be generated by sklearn’s
|
|||
</dl>
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.IndexTransformer.add_word">
|
||||
<span class="sig-name descname"><span class="pre">add_word</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">word</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nogaps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.add_word"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.add_word" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">add_word</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">word</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nogaps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.add_word"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.add_word" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Adds a new token (regardless of whether it has been found in the text or not), with dedicated id.
|
||||
Useful to define special tokens for codifying unknown words, or padding tokens.</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -922,7 +923,7 @@ precedent ids stored so far</p></li>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.IndexTransformer.fit">
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.fit" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.fit" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Fits the transformer, i.e., decides on the vocabulary, given a list of strings.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -936,7 +937,7 @@ precedent ids stored so far</p></li>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.IndexTransformer.fit_transform">
|
||||
<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.fit_transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.fit_transform" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">fit_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.fit_transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.fit_transform" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Fits the transform on <cite>X</cite> and transforms it.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -953,7 +954,7 @@ precedent ids stored so far</p></li>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.IndexTransformer.transform">
|
||||
<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.transform" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">X</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.transform" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Transforms the strings in <cite>X</cite> as lists of numerical ids</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
|
@ -970,7 +971,7 @@ precedent ids stored so far</p></li>
|
|||
|
||||
<dl class="py method">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.IndexTransformer.vocabulary_size">
|
||||
<span class="sig-name descname"><span class="pre">vocabulary_size</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.vocabulary_size"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.vocabulary_size" title="Link to this definition"></a></dt>
|
||||
<span class="sig-name descname"><span class="pre">vocabulary_size</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#IndexTransformer.vocabulary_size"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.IndexTransformer.vocabulary_size" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Gets the length of the vocabulary according to which the document tokens have been indexed</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Returns<span class="colon">:</span></dt>
|
||||
|
|
@ -983,7 +984,7 @@ precedent ids stored so far</p></li>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.index">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.index" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.index" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Indexes the tokens of a textual <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.Dataset</span></code></a> of string documents.
|
||||
To index a document means to replace each different token by a unique numerical index.
|
||||
Rare words (i.e., words occurring less than <cite>min_df</cite> times) are replaced by a special token <cite>UNK</cite></p>
|
||||
|
|
@ -1007,7 +1008,7 @@ are lists of str</p></li>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.reduce_columns">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">reduce_columns</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#reduce_columns"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.reduce_columns" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">reduce_columns</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#reduce_columns"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.reduce_columns" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Reduces the dimensionality of the instances, represented as a <cite>csr_matrix</cite> (or any subtype of
|
||||
<cite>scipy.sparse.spmatrix</cite>), of training and test documents by removing the columns of words which are not present
|
||||
in at least <cite>min_df</cite> instances in the training set</p>
|
||||
|
|
@ -1030,7 +1031,7 @@ in the training set have been removed</p>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.standardize">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">standardize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#standardize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.standardize" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">standardize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#standardize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.standardize" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Standardizes the real-valued columns of a <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.Dataset</span></code></a>.
|
||||
Standardization, aka z-scoring, of a variable <cite>X</cite> comes down to subtracting the average and normalizing by the
|
||||
standard deviation.</p>
|
||||
|
|
@ -1050,7 +1051,7 @@ standard deviation.</p>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.preprocessing.text2tfidf">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">text2tfidf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sublinear_tf</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#text2tfidf"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.text2tfidf" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.preprocessing.</span></span><span class="sig-name descname"><span class="pre">text2tfidf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_df</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sublinear_tf</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/preprocessing.html#text2tfidf"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.preprocessing.text2tfidf" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Transforms a <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.Dataset</span></code></a> of textual instances into a <a class="reference internal" href="#quapy.data.base.Dataset" title="quapy.data.base.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">quapy.data.base.Dataset</span></code></a> of
|
||||
tfidf weighted sparse vectors</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -1074,10 +1075,10 @@ current Dataset (if inplace=True) where the instances are stored in a <cite>csr_
|
|||
|
||||
</section>
|
||||
<section id="module-quapy.data.reader">
|
||||
<span id="quapy-data-reader-module"></span><h2>quapy.data.reader module<a class="headerlink" href="#module-quapy.data.reader" title="Link to this heading"></a></h2>
|
||||
<span id="quapy-data-reader-module"></span><h2>quapy.data.reader module<a class="headerlink" href="#module-quapy.data.reader" title="Permalink to this heading"></a></h2>
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.reader.binarize">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">binarize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pos_class</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#binarize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.binarize" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">binarize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pos_class</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#binarize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.binarize" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Binarizes a categorical array-like collection of labels towards the positive class <cite>pos_class</cite>. E.g.,:</p>
|
||||
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">binarize</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">pos_class</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="gp">>>> </span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
|
||||
|
|
@ -1099,7 +1100,7 @@ current Dataset (if inplace=True) where the instances are stored in a <cite>csr_
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.reader.from_csv">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">from_csv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encoding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'utf-8'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#from_csv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.from_csv" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">from_csv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encoding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'utf-8'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#from_csv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.from_csv" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Reads a csv file in which columns are separated by ‘,’.
|
||||
File format <label>,<feat1>,<feat2>,…,<featn></p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -1117,7 +1118,7 @@ File format <label>,<feat1>,<feat2>,…,<featn></p>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.reader.from_sparse">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">from_sparse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#from_sparse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.from_sparse" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">from_sparse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#from_sparse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.from_sparse" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Reads a labelled collection of real-valued instances expressed in sparse format
|
||||
File format <-1 or 0 or 1>[s col(int):val(float)]</p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -1132,7 +1133,7 @@ File format <-1 or 0 or 1>[s col(int):val(float)]</p>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.reader.from_text">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">from_text</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encoding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'utf-8'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class2int</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#from_text"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.from_text" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">from_text</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encoding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'utf-8'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class2int</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#from_text"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.from_text" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Reads a labelled colletion of documents.
|
||||
File fomart <0 or 1> <document></p>
|
||||
<dl class="field-list simple">
|
||||
|
|
@ -1151,7 +1152,7 @@ File fomart <0 or 1> <document></p>
|
|||
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="quapy.data.reader.reindex_labels">
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">reindex_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#reindex_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.reindex_labels" title="Link to this definition"></a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">quapy.data.reader.</span></span><span class="sig-name descname"><span class="pre">reindex_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">y</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/quapy/data/reader.html#reindex_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#quapy.data.reader.reindex_labels" title="Permalink to this definition"></a></dt>
|
||||
<dd><p>Re-indexes a list of labels as a list of indexes, and returns the classnames corresponding to the indexes.
|
||||
E.g.:</p>
|
||||
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">reindex_labels</span><span class="p">([</span><span class="s1">'B'</span><span class="p">,</span> <span class="s1">'B'</span><span class="p">,</span> <span class="s1">'A'</span><span class="p">,</span> <span class="s1">'C'</span><span class="p">])</span>
|
||||
|
|
@ -1170,7 +1171,7 @@ E.g.:</p>
|
|||
|
||||
</section>
|
||||
<section id="module-quapy.data">
|
||||
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-quapy.data" title="Link to this heading"></a></h2>
|
||||
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-quapy.data" title="Permalink to this heading"></a></h2>
|
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</section>
|
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</section>
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<!DOCTYPE html>
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<html class="writer-html5" lang="en" data-content_root="./">
|
||||
<html class="writer-html5" lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Search — QuaPy: A Python-based open-source framework for quantification 0.1.8 documentation</title>
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=92fd9be5" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css?v=19f00094" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/pygments.css" />
|
||||
<link rel="stylesheet" type="text/css" href="_static/css/theme.css" />
|
||||
|
||||
|
||||
|
||||
|
|
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|
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<script src="_static/js/html5shiv.min.js"></script>
|
||||
<![endif]-->
|
||||
|
||||
<script src="_static/jquery.js?v=5d32c60e"></script>
|
||||
<script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
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<script src="_static/documentation_options.js?v=22607128"></script>
|
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<script src="_static/doctools.js?v=9a2dae69"></script>
|
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<script src="_static/sphinx_highlight.js?v=dc90522c"></script>
|
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<script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
|
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<script src="_static/jquery.js"></script>
|
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<script src="_static/underscore.js"></script>
|
||||
<script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
|
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<script src="_static/doctools.js"></script>
|
||||
<script src="_static/sphinx_highlight.js"></script>
|
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<script src="_static/js/theme.js"></script>
|
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<script src="_static/searchtools.js"></script>
|
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<script src="_static/language_data.js"></script>
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|
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