• datasets subpackage
  • Overview
  • loading_context module
    • DataLoadingContext
      • DataLoadingContext.get_strategy()
      • DataLoadingContext.load_as_np()
      • DataLoadingContext.set_strategy()
      • DataLoadingContext.strategies
    • supported_file_formats()
  • loading_strategies module
    • CSVDataLoadingStrategy
      • CSVDataLoadingStrategy.execute()
    • DataLoadingStrategy
      • DataLoadingStrategy.execute()
  • manager module
    • DatasetsManager
      • DatasetsManager.combine()
      • DatasetsManager.get_column_labels()
      • DatasetsManager.get_dataset_by_type()
      • DatasetsManager.get_info()
      • DatasetsManager.reset()
      • DatasetsManager.reset_datasets()
      • DatasetsManager.save_dataset_to_csv()
      • DatasetsManager.set_column_labels()
      • DatasetsManager.set_from_data()
      • DatasetsManager.set_from_file()
      • DatasetsManager.summarize()
  • masked module
    • MaskedDataset
      • MaskedDataset.clone()
      • MaskedDataset.combine()
      • MaskedDataset.get_confidence_scores()
      • MaskedDataset.get_file_path()
      • MaskedDataset.get_info()
      • MaskedDataset.get_observations()
      • MaskedDataset.get_pseudo_labels()
      • MaskedDataset.get_pseudo_probabilities()
      • MaskedDataset.get_sample_counts()
      • MaskedDataset.get_true_labels()
      • MaskedDataset.refine()
      • MaskedDataset.reset_indices()
      • MaskedDataset.sample_random()
      • MaskedDataset.sample_uniform()
      • MaskedDataset.save_to_csv()
      • MaskedDataset.set_confidence_scores()
      • MaskedDataset.set_file_path()
      • MaskedDataset.set_pseudo_labels()
      • MaskedDataset.set_pseudo_probs_labels()
      • MaskedDataset.summarize()
      • MaskedDataset.to_dataframe()
• models subpackage
  • Overview
  • factories module
    • ModelFactory
      • ModelFactory.create_model_from_pickled()
      • ModelFactory.create_model_with_hyperparams()
      • ModelFactory.factories
      • ModelFactory.get_factory()
      • ModelFactory.get_supported_models()
      • ModelFactory.model_mapping
    • XGBoostFactory
      • XGBoostFactory.check_version()
      • XGBoostFactory.create_model_from_pickled()
      • XGBoostFactory.create_model_with_hyperparams()
      • XGBoostFactory.extract_params()
  • abstract_models module
    • ClassificationModel
      • ClassificationModel.balance_train_weights()
      • ClassificationModel.predict()
      • ClassificationModel.train()
    • Model
      • Model.model
      • Model.model_class
      • Model.params
      • Model.data_preparation_strategy
      • Model.pickled_model
      • Model.evaluate()
      • Model.get_data_strategy()
      • Model.get_info()
      • Model.get_model()
      • Model.get_model_type()
      • Model.get_params()
      • Model.get_path()
      • Model.is_pickled()
      • Model.print_evaluation_results()
      • Model.save()
      • Model.set_data_strategy()
      • Model.set_file_path()
      • Model.set_model()
      • Model.set_params()
      • Model.update_params()
      • Model.validate_params()
    • RegressionModel
      • RegressionModel.predict()
      • RegressionModel.train()
  • concrete_classifiers module
    • XGBoostModel
      • XGBoostModel.evaluate()
      • XGBoostModel.predict()
      • XGBoostModel.train()
      • XGBoostModel.train_to_disagree()
  • concrete_regressors module
    • DecisionTreeRegressorModel
      • DecisionTreeRegressorModel.evaluate()
      • DecisionTreeRegressorModel.predict()
      • DecisionTreeRegressorModel.train()
    • RandomForestRegressorModel
      • RandomForestRegressorModel.evaluate()
      • RandomForestRegressorModel.predict()
      • RandomForestRegressorModel.train()
  • abstract_metrics module
    • EvaluationMetric
      • EvaluationMetric.get_metric()
      • EvaluationMetric.supported_metrics()
  • classification_metrics module
    • ClassificationEvaluationMetrics
      • ClassificationEvaluationMetrics.accuracy()
      • ClassificationEvaluationMetrics.average_precision()
      • ClassificationEvaluationMetrics.balanced_accuracy()
      • ClassificationEvaluationMetrics.f1_score()
      • ClassificationEvaluationMetrics.get_metric()
      • ClassificationEvaluationMetrics.log_loss()
      • ClassificationEvaluationMetrics.matthews_corrcoef()
      • ClassificationEvaluationMetrics.npv()
      • ClassificationEvaluationMetrics.ppv()
      • ClassificationEvaluationMetrics.precision()
      • ClassificationEvaluationMetrics.recall()
      • ClassificationEvaluationMetrics.roc_auc()
      • ClassificationEvaluationMetrics.sensitivity()
      • ClassificationEvaluationMetrics.specificity()
      • ClassificationEvaluationMetrics.supported_metrics()
  • regression_metrics module
    • RegressionEvaluationMetrics
      • RegressionEvaluationMetrics.get_metric()
      • RegressionEvaluationMetrics.mean_absolute_error()
      • RegressionEvaluationMetrics.mean_squared_error()
      • RegressionEvaluationMetrics.r2_score()
      • RegressionEvaluationMetrics.root_mean_squared_error()
      • RegressionEvaluationMetrics.supported_metrics()
  • data_strategies module
    • DataPreparingStrategy
      • DataPreparingStrategy.execute()
    • ToDataframesStrategy
      • ToDataframesStrategy.execute()
    • ToDmatrixStrategy
      • ToDmatrixStrategy.execute()
      • ToDmatrixStrategy.is_supported_data()
    • ToNumpyStrategy
      • ToNumpyStrategy.execute()
  • base module
    • BaseModelManager
      • BaseModelManager.clone_base_model()
      • BaseModelManager.get_instance()
      • BaseModelManager.reset()
      • BaseModelManager.set_base_model()
• detectron subpackage
  • Overview
  • ensemble module
    • DetectronEnsemble
      • DetectronEnsemble.evaluate_ensemble()
  • record module
    • DetectronRecord
      • DetectronRecord.to_dict()
      • DetectronRecord.update()
    • DetectronRecordsManager
      • DetectronRecordsManager.count_quantile()
      • DetectronRecordsManager.counts()
      • DetectronRecordsManager.freeze()
      • DetectronRecordsManager.get_evaluation()
      • DetectronRecordsManager.get_record()
      • DetectronRecordsManager.load()
      • DetectronRecordsManager.predicted_probabilities()
      • DetectronRecordsManager.rejected_count_quantile()
      • DetectronRecordsManager.rejected_counts()
      • DetectronRecordsManager.rejection_rates()
      • DetectronRecordsManager.save()
      • DetectronRecordsManager.seed()
      • DetectronRecordsManager.set_evaluation()
      • DetectronRecordsManager.update()
  • stopper module
    • EarlyStopper
      • EarlyStopper.update()
  • strategies module
  • experiment module
  • comparaison module
• med3pa subpackage
  • Overview
    • Key Components:
    • Advanced Analysis with MDR:
    • Extensibility for Integration:
  • uncertainty module
    • AbsoluteError
      • AbsoluteError.calculate()
    • UncertaintyCalculator
      • UncertaintyCalculator.calculate_uncertainty()
      • UncertaintyCalculator.metric_mapping
      • UncertaintyCalculator.supported_metrics()
    • UncertaintyMetric
      • UncertaintyMetric.calculate()
  • models module
    • APCModel
      • APCModel.default_params
      • APCModel.evaluate()
      • APCModel.get_info()
      • APCModel.load_model()
      • APCModel.load_tree()
      • APCModel.optimize()
      • APCModel.predict()
      • APCModel.print_decision_tree_structure()
      • APCModel.save_model()
      • APCModel.supported_models_params()
      • APCModel.supported_params
      • APCModel.train()
    • IPCModel
      • IPCModel.default_params
      • IPCModel.evaluate()
      • IPCModel.get_info()
      • IPCModel.load_model()
      • IPCModel.optimize()
      • IPCModel.predict()
      • IPCModel.save_model()
      • IPCModel.supported_ipc_models()
      • IPCModel.supported_models_params()
      • IPCModel.supported_regressors_mapping
      • IPCModel.supported_regressos_params
      • IPCModel.train()
      • IPCModel.underlying_models_mapping
    • MPCModel
      • MPCModel.predict()
  • tree module
    • TreeRepresentation
      • TreeRepresentation.build_tree()
      • TreeRepresentation.get_all_nodes()
      • TreeRepresentation.get_all_profiles()
      • TreeRepresentation.save_tree()
    • to_serializable()
  • Profiles module
    • Profile
      • Profile.to_dict()
      • Profile.update_detectron_results()
      • Profile.update_metrics_results()
      • Profile.update_node_information()
    • ProfilesManager
      • ProfilesManager.get_lost_profiles()
      • ProfilesManager.get_profiles()
      • ProfilesManager.insert_lost_profiles()
      • ProfilesManager.insert_profiles()
      • ProfilesManager.transform_to_profiles()
  • MDR module
    • MDRCalculator
      • MDRCalculator.calc_metrics_by_dr()
      • MDRCalculator.calc_metrics_by_profiles()
      • MDRCalculator.calc_profiles()
      • MDRCalculator.calc_profiles_deprecated()
      • MDRCalculator.detectron_by_profiles()
      • MDRCalculator.detectron_by_profiles_deprecated()
      • MDRCalculator.update_min_confidence()
  • experiment module
    • Med3paDetectronExperiment
      • Med3paDetectronExperiment.run()
    • Med3paExperiment
      • Med3paExperiment.run()
    • Med3paRecord
      • Med3paRecord.get_confidence_scores()
      • Med3paRecord.get_profiles_manager()
      • Med3paRecord.save()
      • Med3paRecord.set_confidence_scores()
      • Med3paRecord.set_dataset()
      • Med3paRecord.set_metrics_by_dr()
      • Med3paRecord.set_models_evaluation()
      • Med3paRecord.set_profiles_manager()
      • Med3paRecord.set_tree()
    • Med3paResults
      • Med3paResults.os
      • Med3paResults.save()
      • Med3paResults.save_models()
      • Med3paResults.set_detectron_results()
      • Med3paResults.set_experiment_config()
      • Med3paResults.set_models()
    • to_serializable()
  • compraison module
    • Med3paComparison
      • Med3paComparison.compare_config()
      • Med3paComparison.compare_experiments()
      • Med3paComparison.compare_global_metrics()
      • Med3paComparison.compare_models_evaluation()
      • Med3paComparison.compare_profiles_detectron_results()
      • Med3paComparison.compare_profiles_metrics()
      • Med3paComparison.identify_shared_profiles()
      • Med3paComparison.is_comparable()
      • Med3paComparison.save()