pyriemann_qiskit.utils.transfer.TLCrossSubjectEvaluation¶

class pyriemann_qiskit.utils.transfer.TLCrossSubjectEvaluation(paradigm: BaseParadigm, datasets: list[BaseDataset] | None = None, random_state: int | None = None, n_jobs: int = 1, overwrite: bool = False, error_score: str | float = 'raise', suffix: str = '', hdf5_path: str | None = None, additional_columns: list[str] | None = None, return_epochs: bool = False, return_raws: bool = False, mne_labels: bool = False, n_splits: int | None = None, cv_class: type | None = None, cv_kwargs: dict | None = None, save_model: bool = False, cache_config: CacheConfig | None = None, optuna: bool = False, time_out: int = 900, verbose: bool | str | int | None = None, codecarbon_config: dict | None = None)[source]¶

CrossSubjectEvaluation with group and target-domain forwarding.

Extends CrossSubjectEvaluation with one behavioural change:

Pipelines whose fit() declares groups receive the training subject IDs. Pipelines whose fit() also declares target_domain receive the test subject’s ID as target_domain. All other pipelines are unaffected.

**kwargs: Forwarded to CrossSubjectEvaluation.__init__().

__init__(paradigm: BaseParadigm, datasets: list[BaseDataset] | None = None, random_state: int | None = None, n_jobs: int = 1, overwrite: bool = False, error_score: str | float = 'raise', suffix: str = '', hdf5_path: str | None = None, additional_columns: list[str] | None = None, return_epochs: bool = False, return_raws: bool = False, mne_labels: bool = False, n_splits: int | None = None, cv_class: type | None = None, cv_kwargs: dict | None = None, save_model: bool = False, cache_config: CacheConfig | None = None, optuna: bool = False, time_out: int = 900, verbose: bool | str | int | None = None, codecarbon_config: dict | None = None)¶