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River2SKLTransformer

Compatibility layer from River to scikit-learn for transformation.

Parameters

Methods

fit

Fits to an entire dataset contained in memory.

Parameters

  • X
  • y — defaults to None

Returns

self

fit_transform

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.

Parameters

  • X
  • y — defaults to None
  • fit_params

Returns

ndarray array of shape (n_samples, n_features_new)

get_metadata_routing

Get metadata routing of this object.

Please check :ref:User Guide <metadata_routing> on how the routing mechanism works.

Returns

MetadataRequest

get_params

Get parameters for this estimator.

Parameters

  • deep — defaults to True

Returns

dict

partial_fit

Fits incrementally on a portion of a dataset.

Parameters

  • X
  • y — defaults to None

Returns

self

set_output

Set output container.

See :ref:sphx_glr_auto_examples_miscellaneous_plot_set_output.py for an example on how to use the API.

Parameters

  • transform — defaults to None

Returns

estimator instance

set_params

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as :class:~sklearn.pipeline.Pipeline). The latter have parameters of the form <component>__<parameter> so that it's possible to update each component of a nested object.

Parameters

  • params

Returns

estimator instance

transform

Predicts the target of an entire dataset contained in memory.

Parameters

  • X

Returns

Transformed output.