mlcompare.full_pipeline

mlcompare.full_pipeline(dataset_params, model_params, task_type, save_models='none', save_original=True, save_processed=True, save_directory=None)

A pipeline with data retrieval, processing, model training and model evaluation.

Return type:

None

Parameters:

• dataset_params (list[dict[str, Any]] | str | Path)

• model_params (list[dict[str, Any]] | str | Path)

• task_type (Literal['classification', 'regression'])

• save_models (Literal['all', 'best', 'none'])

• save_original (bool)

• save_processed (bool)

• save_directory (str | Path | None)

Args:

dataset_params (ParamsInput): List containing dataset information. model_params (ParamsInput): List containing model information. task_type (Literal[“classification”, “regression”]): Type of machine learning task to be performed. save_models (Literal[“all”, “best”, “none”], optional): Save all models, only the best model, or no models. Defaults to “none”. save_original (bool, optional): Save original datasets. Defaults to True. save_processed (bool, optional): Save processed datasets. Defaults to True. save_directory (str | Path, optional): Directory to save data, models, and results to. Defaults to “mlc-y-m-DTH-M-S-MS”.