pyeeg.models.TRFEstimator.set_fit_request

TRFEstimator.set_fit_request(*, cache_lagged: bool | None | str = '$UNCHANGED$', drop: bool | None | str = '$UNCHANGED$', feat_names: bool | None | str = '$UNCHANGED$', lagged: bool | None | str = '$UNCHANGED$', rotations: bool | None | str = '$UNCHANGED$', weights: bool | None | str = '$UNCHANGED$') → TRFEstimator

Configure whether metadata should be requested to be passed to the fit method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters:

  • cache_lagged (str, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED) – Metadata routing for cache_lagged parameter in fit.

  • drop (str, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED) – Metadata routing for drop parameter in fit.

  • feat_names (str, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED) – Metadata routing for feat_names parameter in fit.

  • lagged (str, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED) – Metadata routing for lagged parameter in fit.

  • rotations (str, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED) – Metadata routing for rotations parameter in fit.

  • weights (str, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED) – Metadata routing for weights parameter in fit.

Returns:

self – The updated object.

Return type:

object