Med3pa documentation

Installation Guide

  • Installation Guide

Subpackages

  • datasets subpackage
  • models subpackage
  • detectron subpackage
  • med3pa subpackage

Tutorials

  • Working with datasets subpackage
  • Working with the Models Subpackage
  • Working with the Detectron Subpackage
  • Working with the med3pa Subpackage
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  • 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()
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