pyeeg.cca.CCA_Estimator.set_transform_request

CCA_Estimator.set_transform_request(*, comp: bool | None | str = '$UNCHANGED$', transform_x: bool | None | str = '$UNCHANGED$', transform_y: bool | None | str = '$UNCHANGED$') → CCA_Estimator

Configure whether metadata should be requested to be passed to the transform 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 transform 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 transform.

  • 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:

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

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

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

Returns:

self – The updated object.

Return type:

object