INNER CODE UNIT · Python
_train_pipeline_on_full_dataset
aimclub/FEDOT · fedot/api/main.py:566
def _train_pipeline_on_full_dataset(self, recommendations: Optional[dict],
full_train_not_preprocessed: Union[InputData, MultiModalData]):
"""Applies training procedure for obtained pipeline if dataset was clipped
"""
if recommendations is not None:
# if data was cut we need to refit pipeline on full data
self.data_processor.accept_and_apply_recommendations(full_train_not_preprocessed,
{k: v for k, v in recommendations.items()
if k != 'cut'})
self.current_pipeline.fit(
full_train_not_preprocessed,
n_jobs=self.params.n_jobs
)