immuneML.hyperparameter_optimization.states package

Submodules

immuneML.hyperparameter_optimization.states.HPAssessmentState module

class immuneML.hyperparameter_optimization.states.HPAssessmentState.HPAssessmentState(split_index: int, train_val_dataset, test_dataset, path: Path, label_configuration: LabelConfiguration)[source]: Bases: object

immuneML.hyperparameter_optimization.states.HPItem module

class immuneML.hyperparameter_optimization.states.HPItem.HPItem(method: immuneML.ml_methods.MLMethod.MLMethod = None, encoder: immuneML.encodings.DatasetEncoder.DatasetEncoder = None, performance: dict = None, hp_setting: immuneML.hyperparameter_optimization.HPSetting.HPSetting = None, train_predictions_path: pathlib.Path = None, test_predictions_path: pathlib.Path = None, ml_details_path: pathlib.Path = None, train_dataset: immuneML.data_model.dataset.Dataset.Dataset = None, test_dataset: immuneML.data_model.dataset.Dataset.Dataset = None, split_index: int = None, model_report_results: List[immuneML.reports.ReportResult.ReportResult] = <factory>, encoding_train_results: List[immuneML.reports.ReportResult.ReportResult] = <factory>, encoding_test_results: List[immuneML.reports.ReportResult.ReportResult] = <factory>)[source]

Bases: object

encoder: DatasetEncoder = None

encoding_test_results: List[ReportResult]

encoding_train_results: List[ReportResult]

hp_setting: HPSetting = None

method: MLMethod = None

ml_details_path: Path = None

model_report_results: List[ReportResult]

performance: dict = None

split_index: int = None

test_dataset: Dataset = None

test_predictions_path: Path = None

train_dataset: Dataset = None

train_predictions_path: Path = None

immuneML.hyperparameter_optimization.states.HPLabelState module

class immuneML.hyperparameter_optimization.states.HPLabelState.HPLabelState(label, auxiliary_labels)[source]

Bases: object

property optimal_assessment_item

property optimal_hp_setting

immuneML.hyperparameter_optimization.states.HPSelectionState module

class immuneML.hyperparameter_optimization.states.HPSelectionState.HPSelectionState(train_datasets, val_datasets, path: Path, hp_strategy: HPOptimizationStrategy)[source]

Bases: object

property optimal_hp_setting

immuneML.hyperparameter_optimization.states.TrainMLModelState module

class immuneML.hyperparameter_optimization.states.TrainMLModelState.TrainMLModelState(dataset: immuneML.data_model.dataset.Dataset.Dataset, hp_strategy: immuneML.hyperparameter_optimization.strategy.HPOptimizationStrategy.HPOptimizationStrategy, hp_settings: List[immuneML.hyperparameter_optimization.HPSetting.HPSetting], assessment: immuneML.hyperparameter_optimization.config.SplitConfig.SplitConfig, selection: immuneML.hyperparameter_optimization.config.SplitConfig.SplitConfig, metrics: Set[immuneML.ml_metrics.Metric.Metric], optimization_metric: immuneML.ml_metrics.Metric.Metric, label_configuration: immuneML.environment.LabelConfiguration.LabelConfiguration, path: pathlib.Path = None, context: dict = None, number_of_processes: int = 1, reports: dict = <factory>, name: str = None, refit_optimal_model: bool = None, optimal_hp_items: Dict[str, immuneML.hyperparameter_optimization.states.HPItem.HPItem] = <factory>, optimal_hp_item_paths: Dict[str, str] = <factory>, assessment_states: List[immuneML.hyperparameter_optimization.states.HPAssessmentState.HPAssessmentState] = <factory>, report_results: List[immuneML.reports.ReportResult.ReportResult] = <factory>)[source]