forked from moreo/QuaPy
svmperf in one-vs-all bugfix
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@ -85,4 +85,5 @@ Things to fix:
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--------------
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- update unit tests
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- improve plots
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- svmperf clean temp dirs; check also ELM when instantiated using SVMperf directly
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@ -880,16 +880,27 @@ class ELM(AggregativeQuantifier, BinaryQuantifier):
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learning algorithm, which has to be installed and patched for the purpose (see this
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`script <https://github.com/HLT-ISTI/QuaPy/blob/master/prepare_svmperf.sh>`_).
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:param classifier: an instance of `SVM perf` or None
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:param svmperf_base: path to the folder containing the binary files of `SVM perf`
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:param loss: the loss to optimize (see :attr:`quapy.classification.svmperf.SVMperf.valid_losses`)
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:param kwargs: rest of SVM perf's parameters
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"""
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def __init__(self, svmperf_base=None, loss='01', **kwargs):
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def __init__(self, classifier=None, svmperf_base=None, loss='01', **kwargs):
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self.svmperf_base = svmperf_base if svmperf_base is not None else qp.environ['SVMPERF_HOME']
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self.loss = loss
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self.kwargs = kwargs
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assert classifier is None or isinstance(classifier, SVMperf), \
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'param error "classifier": instances of ELM can only be instantiated with classifier SVMperf. ' \
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'This parameter should either be an instance of SVMperf or None, in which case an SVMperf object ' \
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'will be instantiaded using "svmperf_base" and "loss"'
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if classifier is None:
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self.classifier = SVMperf(self.svmperf_base, loss=self.loss, **self.kwargs)
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else:
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if classifier.loss != loss:
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print(f'[warning]: the loss of the SVMperf object passed to arg "classifier" ({classifier.loss}) '
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f'does not coincide with arg "loss" ({loss}); the latter will be ignored')
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self.classifier = classifier
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def fit(self, data: LabelledCollection, fit_classifier=True):
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self._check_binary(data, self.__class__.__name__)
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@ -913,11 +924,14 @@ class SVMQ(ELM):
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>>> ELM(svmperf_base, loss='q', **kwargs)
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:param classifier: not used, added for compatibility
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:param svmperf_base: path to the folder containing the binary files of `SVM perf`
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:param kwargs: rest of SVM perf's parameters
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"""
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def __init__(self, svmperf_base=None, **kwargs):
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def __init__(self, classifier=None, svmperf_base=None, **kwargs):
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assert classifier == None, \
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'param "classifier" should be None. SVMperf will be instantiated using "svmperf_base" path.'
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super(SVMQ, self).__init__(svmperf_base, loss='q', **kwargs)
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@ -929,11 +943,14 @@ class SVMKLD(ELM):
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>>> ELM(svmperf_base, loss='kld', **kwargs)
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:param classifier: not used, added for compatibility
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:param svmperf_base: path to the folder containing the binary files of `SVM perf`
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:param kwargs: rest of SVM perf's parameters
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"""
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def __init__(self, svmperf_base=None, **kwargs):
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def __init__(self, classifier=None, svmperf_base=None, **kwargs):
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assert classifier == None, \
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'param "classifier" should be None. SVMperf will be instantiated using "svmperf_base" path.'
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super(SVMKLD, self).__init__(svmperf_base, loss='kld', **kwargs)
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@ -946,11 +963,14 @@ class SVMNKLD(ELM):
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>>> ELM(svmperf_base, loss='nkld', **kwargs)
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:param classifier: not used, added for compatibility
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:param svmperf_base: path to the folder containing the binary files of `SVM perf`
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:param kwargs: rest of SVM perf's parameters
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"""
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def __init__(self, svmperf_base=None, **kwargs):
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def __init__(self, classifier=None, svmperf_base=None, **kwargs):
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assert classifier == None, \
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'param "classifier" should be None. SVMperf will be instantiated using "svmperf_base" path.'
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super(SVMNKLD, self).__init__(svmperf_base, loss='nkld', **kwargs)
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@ -962,11 +982,14 @@ class SVMAE(ELM):
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>>> ELM(svmperf_base, loss='mae', **kwargs)
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:param classifier: not used, added for compatibility
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:param svmperf_base: path to the folder containing the binary files of `SVM perf`
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:param kwargs: rest of SVM perf's parameters
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"""
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def __init__(self, svmperf_base=None, **kwargs):
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def __init__(self, classifier=None, svmperf_base=None, **kwargs):
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assert classifier == None, \
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'param "classifier" should be None. SVMperf will be instantiated using "svmperf_base" path.'
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super(SVMAE, self).__init__(svmperf_base, loss='mae', **kwargs)
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@ -978,11 +1001,14 @@ class SVMRAE(ELM):
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>>> ELM(svmperf_base, loss='mrae', **kwargs)
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:param classifier: not used, added for compatibility
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:param svmperf_base: path to the folder containing the binary files of `SVM perf`
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:param kwargs: rest of SVM perf's parameters
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"""
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def __init__(self, svmperf_base=None, **kwargs):
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def __init__(self, classifier=None, svmperf_base=None, **kwargs):
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assert classifier == None, \
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'param "classifier" should be None. SVMperf will be instantiated using "svmperf_base" path.'
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super(SVMRAE, self).__init__(svmperf_base, loss='mrae', **kwargs)
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