dtoolkit.pipeline.Pipeline.decision_function

Pipeline.decision_function(X, **params)

Transform the data, and apply decision_function with the final estimator.

Call transform of each transformer in the pipeline. The transformed data are finally passed to the final estimator that calls decision_function method. Only valid if the final estimator implements decision_function.

Parameters:

Xiterable

Data to predict on. Must fulfill input requirements of first step of the pipeline.

**paramsdict of string -> object

Parameters requested and accepted by steps. Each step must have requested certain metadata for these parameters to be forwarded to them.

New in version 1.4: Only available if enable_metadata_routing=True. See Metadata Routing User Guide for more details.

Returns:

y_scorendarray of shape (n_samples, n_classes)

Result of calling decision_function on the final estimator.