quapy

• quapy package
  • Subpackages
    • quapy.classification package
      • Submodules
      • quapy.classification.calibration module
      • quapy.classification.methods module
      • quapy.classification.neural module
      • quapy.classification.svmperf module
      • Module contents
    • quapy.data package
      • Submodules
      • quapy.data.base module
      • quapy.data.datasets module
      • quapy.data.preprocessing module
      • quapy.data.reader module
      • Module contents
    • quapy.method package
      • Submodules
      • quapy.method.aggregative module
      • quapy.method.base module
      • quapy.method.meta module
      • quapy.method.non_aggregative module
      • Module contents
  • Submodules
  • quapy.error module
    • absolute_error()
    • acc_error()
    • acce()
    • ae()
    • f1_error()
    • f1e()
    • from_name()
    • kld()
    • mae()
    • mean_absolute_error()
    • mean_normalized_absolute_error()
    • mean_normalized_relative_absolute_error()
    • mean_relative_absolute_error()
    • mkld()
    • mnae()
    • mnkld()
    • mnrae()
    • mrae()
    • mse()
    • nae()
    • nkld()
    • normalized_absolute_error()
    • normalized_relative_absolute_error()
    • nrae()
    • rae()
    • relative_absolute_error()
    • se()
    • smooth()
  • quapy.evaluation module
    • evaluate()
    • evaluate_on_samples()
    • evaluation_report()
    • prediction()
  • quapy.functional module
    • HellingerDistance()
    • TopsoeDistance()
    • adjusted_quantification()
    • argmin_prevalence()
    • as_binary_prevalence()
    • check_prevalence_vector()
    • get_divergence()
    • get_nprevpoints_approximation()
    • linear_search()
    • normalize_prevalence()
    • num_prevalence_combinations()
    • optim_minimize()
    • prevalence_from_labels()
    • prevalence_from_probabilities()
    • prevalence_linspace()
    • strprev()
    • uniform_prevalence_sampling()
    • uniform_simplex_sampling()
  • quapy.model_selection module
    • ConfigStatus
      • ConfigStatus.failed()
      • ConfigStatus.success()
    • GridSearchQ
      • GridSearchQ.best_model()
      • GridSearchQ.fit()
      • GridSearchQ.get_params()
      • GridSearchQ.quantify()
      • GridSearchQ.set_params()
    • Status
      • Status.ERROR
      • Status.INVALID
      • Status.SUCCESS
      • Status.TIMEOUT
    • cross_val_predict()
    • expand_grid()
    • group_params()
  • quapy.plot module
    • binary_bias_bins()
    • binary_bias_global()
    • binary_diagonal()
    • brokenbar_supremacy_by_drift()
    • error_by_drift()
  • quapy.protocol module
    • APP
      • APP.prevalence_grid()
      • APP.sample()
      • APP.samples_parameters()
      • APP.total()
    • AbstractProtocol
      • AbstractProtocol.total()
    • AbstractStochasticSeededProtocol
      • AbstractStochasticSeededProtocol.collator()
      • AbstractStochasticSeededProtocol.random_state
      • AbstractStochasticSeededProtocol.sample()
      • AbstractStochasticSeededProtocol.samples_parameters()
    • ArtificialPrevalenceProtocol
    • DomainMixer
      • DomainMixer.sample()
      • DomainMixer.samples_parameters()
      • DomainMixer.total()
    • IterateProtocol
      • IterateProtocol.total()
    • NPP
      • NPP.sample()
      • NPP.samples_parameters()
      • NPP.total()
    • NaturalPrevalenceProtocol
    • OnLabelledCollectionProtocol
      • OnLabelledCollectionProtocol.RETURN_TYPES
      • OnLabelledCollectionProtocol.get_collator()
      • OnLabelledCollectionProtocol.get_labelled_collection()
      • OnLabelledCollectionProtocol.on_preclassified_instances()
    • UPP
      • UPP.sample()
      • UPP.samples_parameters()
      • UPP.total()
    • UniformPrevalenceProtocol
  • quapy.util module
    • EarlyStop
    • create_if_not_exist()
    • create_parent_dir()
    • download_file()
    • download_file_if_not_exists()
    • get_quapy_home()
    • map_parallel()
    • parallel()
    • pickled_resource()
    • save_text_file()
    • temp_seed()
    • timeout()
  • Module contents