Model combiners#

swectral.combine_classifier(...[, ...])

Combine trainable data preprocessing models with a classifier into a unified estimator that preserves component names.

swectral.combine_regressor(...[, ...])

Combine trainable data preprocessing models with a regressor into a unified estimator that preserves component names.

swectral.IdentityTransformer()

A passthrough scikit-learn-style transformer that returns the input data unchanged.

swectral.IdentityResampler()

A passthrough imblearn-style resampler that returns the input data unchanged.

swectral.modelcombiners.create_bagging_model(...)

Create a bagging model instance from specified base_estimator.

swectral.modelcombiners.BaggingEnsembler(...)

Bagging ensemble for regression and classification models with options of feature resampling.

swectral.modelcombiners.regressor_to_classifier(...)

Create a classifier from a numpy-style regressor using one-hot encoding and probability regression.

swectral.modelcombiners.RegressorToClassifier(...)

Wrap a sklearn-style regressor into a sklearn-style classifier using one-hot encoding and probability regression.