dtoolkit.pipeline.Pipeline.fit_transform

Pipeline.fit_transform(X, y=None, **params) → ndarray | Series | DataFrame

Fit the model and transform with the final estimator.

Fit all the transformers one after the other and sequentially transform the data. Only valid if the final estimator either implements fit_transform or fit and transform.

Parameters:

Xiterable

Training data. Must fulfill input requirements of first step of the pipeline.

yiterable, default=None

Training targets. Must fulfill label requirements for all steps of the pipeline.

**paramsdict of str -> object

• If enable_metadata_routing=False (default):

  Parameters passed to the fit method of each step, where each parameter name is prefixed such that parameter p for step s has key s__p.

• If enable_metadata_routing=True:

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

Changed in version 1.4: Parameters are now passed to the transform method of the intermediate steps as well, if requested, and if enable_metadata_routing=True.

See Metadata Routing User Guide for more details.

Returns:

Xtndarray of shape (n_samples, n_transformed_features)

Transformed samples.