surrogate.pipeline

surrogate.pipeline

Classes

Name	Description
Pipeline	Pipeline of transforms with a final estimator.

Pipeline

surrogate.pipeline.Pipeline(steps)

Pipeline of transforms with a final estimator.

Sequentially apply a list of transforms and a final estimator. This simple implementation assumes that all steps except the last one are transformers (have fit_transform or fit+transform), and the last step is an estimator (has fit and predict).

Parameters

Name	Type	Description	Default
steps	list	List of (name, transform) tuples (implementing fit/transform) that are chained, in the order they are chained, with the last object an estimator.	required

Methods

Name	Description
fit	Fit the model.
predict	Transform the data, and apply predict with the final estimator.

fit

surrogate.pipeline.Pipeline.fit(X, y=None, **fit_params)

Fit the model.

Fit all the transformers one after the other and transform the data. Finally, fit the transformed data using the final estimator.

Parameters

Name	Type	Description	Default
X	iterable	Training data. Must fulfill input requirements of first step of the pipeline.	required
y	iterable	Training targets. Must fulfill label requirements for all steps of the pipeline.	None
**fit_params	Any	Additional parameters passed to the fit method of the final estimator.	{}

Returns

Name	Type	Description
Pipeline	Pipeline	Pipeline with fitted steps.

predict

surrogate.pipeline.Pipeline.predict(X, **predict_params)

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

Parameters

Name	Type	Description	Default
X	iterable	Data to predict on. Must fulfill input requirements of first step of the pipeline.	required
**predict_params	Any	Additional parameters passed to the predict method of the final estimator.	{}

Returns

Name	Type	Description
Any	Any	Result of calling predict on the final estimator.