dtoolkit.pipeline.Pipeline#
- class dtoolkit.pipeline.Pipeline(steps, *, memory=None, verbose=False)[source]#
Pipeline of transforms with a final estimator.
- Parameters:
- *args, **kwargs
See the documentation for
sklearn.pipeline.Pipeline
for complete details on the positional arguments and keyword arguments.
See also
make_pipeline
DToolKit’s version
sklearn.pipeline.make_pipeline
sklearn’s version
Notes
Different to
sklearn.pipeline.Pipeline
. This would letDataFrame
in andDataFrame
out.- Attributes:
classes_
The classes labels.
feature_names_in_
Names of features seen during first step fit method.
n_features_in_
Number of features seen during first step fit method.
named_steps
Access the steps by name.
Methods
decision_function
(X, **params)Transform the data, and apply decision_function with the final estimator.
fit
(X[, y])Fit the model.
fit_predict
(X[, y])Transform the data, and apply predict with the final estimator.
fit_transform
(X[, y])Fit the model and transform with the final estimator.
get_feature_names_out
([input_features])Get output feature names for transformation.
Get metadata routing of this object.
get_params
([deep])Get parameters for this estimator.
inverse_transform
(Xt, **params)Apply inverse_transform for each step in a reverse order.
predict
(X, **params)Transform the data, and apply predict with the final estimator.
predict_log_proba
(X, **params)Transform the data, and apply predict_log_proba with the final estimator.
predict_proba
(X, **params)Transform the data, and apply predict_proba with the final estimator.
score
(X[, y, sample_weight])Transform the data, and apply score with the final estimator.
Transform the data, and apply score_samples with the final estimator.
set_output
(*[, transform])Set the output container when "transform" and "fit_transform" are called.
set_params
(**kwargs)Set the parameters of this estimator.
set_score_request
(*[, sample_weight])Request metadata passed to the
score
method.transform
(X, **params)Transform the data, and apply transform with the final estimator.