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

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:

  • 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