API documentation

wolpert.pipeline: Pipeline classes and utility functions

Classes

StackingLayer(transformer_list[, n_jobs, …])	Creates a single layer for the stacked ensemble.
StackingPipeline(steps[, memory])	A pipeline of ``StackingLayer``s with a final estimator.

Functions

make_stack_layer(*estimators, **kwargs)

Creates a single stack layer to be used in a stacked ensemble.

wolpert.wrappers: Wrappers

Classes

HoldoutWrapper([default_method, …])	Helper class to wrap estimators with HoldoutStackableTransformer
CVWrapper([default_method, default_scoring, …])	Helper class to wrap estimators with CVStackableTransformer
TimeSeriesWrapper([default_method, …])	Helper class to wrap estimators with TimeSeriesStackableTransformer
HoldoutStackableTransformer(estimator[, …])	Transformer to turn estimators into meta-estimators for model stacking
CVStackableTransformer(estimator[, method, …])	Transformer to turn estimators into meta-estimators for model stacking
TimeSeriesStackableTransformer(estimator[, …])	Transformer to turn estimators into meta-estimators for model stacking