pyeeg.cca.CCA_Estimator.set_fit_request

CCA_Estimator.set_fit_request(*, cca_implementation: bool | None | str = '$UNCHANGED$', drop: bool | None | str = '$UNCHANGED$', feat_names: bool | None | str = '$UNCHANGED$', knee_point: bool | None | str = '$UNCHANGED$', lag_y: bool | None | str = '$UNCHANGED$', n_comp: bool | None | str = '$UNCHANGED$', normalise: bool | None | str = '$UNCHANGED$', opt_cca_svd: bool | None | str = '$UNCHANGED$', thresh_x: bool | None | str = '$UNCHANGED$', thresh_y: bool | None | str = '$UNCHANGED$', y_already_dropped: bool | None | str = '$UNCHANGED$', ylags: bool | None | str = '$UNCHANGED$') → CCA_Estimator

Request metadata passed to the fit method.

Note that this method is only relevant if enable_metadata_routing=True (see sklearn.set_config()). Please see 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.

Note

This method is only relevant if this estimator is used as a sub-estimator of a meta-estimator, e.g. used inside a Pipeline. Otherwise it has no effect.

Parameters:

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

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

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

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

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

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

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

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

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

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

Returns:

self – The updated object.

Return type:

object