SklearnPreprocessingPerIntervalModel

class SklearnPreprocessingPerIntervalModel(preprocessing: sklearn.base.TransformerMixin)

Bases: etna.transforms.decomposition.change_points_based.per_interval_models.base.PerIntervalModel

SklearnPreprocessingPerIntervalModel applies PerIntervalModel interface for sklearn preprocessings.

Inherited-members

Parameters

preprocessing (sklearn.base.TransformerMixin) –

Methods

fit(features, target, *args, **kwargs)	Fit preprocessing with given features and targets.
inverse(features)	Apply inverse transformation.
predict(features, *args, **kwargs)	Apply preprocessing to given features.
set_params(**params)	Return new object instance with modified parameters.
to_dict()	Collect all information about etna object in dict.

fit(features: numpy.ndarray, target: numpy.ndarray, *args, **kwargs) → etna.transforms.decomposition.change_points_based.per_interval_models.sklearn_based.SklearnPreprocessingPerIntervalModel

Fit preprocessing with given features and targets.

Parameters

• features (numpy.ndarray) – features to fit preprocessing with

• target (numpy.ndarray) – targets to apply preprocessing to

Returns

fitted SklearnPreprocessingPerIntervalModel

Return type

self

inverse(features: numpy.ndarray) → numpy.ndarray

Apply inverse transformation.

Parameters

features (numpy.ndarray) – features to apply inverse transformation

Returns

features after inverse transformation

Return type

inversed data

predict(features: numpy.ndarray, *args, **kwargs) → numpy.ndarray

Apply preprocessing to given features.

Parameters

features (numpy.ndarray) – features to make preprocessing for

Returns

preprocessing’s prediction for given features

Return type

prediction