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scikit-learn 1.3.2
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# `sklearn.base`.BaseEstimator

class sklearn.base.BaseEstimator

  Base class for all estimators in scikit-learn.

  Notes

  All estimators should specify all the parameters that can be set at the class level in their `__init__` as explicit keyword arguments (no `*args` or `**kwargs`).

  Methods

  `get_metadata_routing`() | Get metadata routing of this object.
  `get_params`([deep]) | Get parameters for this estimator.
  `set_params`(**params) | Set the parameters of this estimator.

  get_metadata_routing()

    Get metadata routing of this object.

    Please check User Guide on how the routing mechanism works.

    Returns:
      routing MetadataRequest

        A `MetadataRequest` encapsulating routing information.

  get_params(deep=True)

    Get parameters for this estimator.

    Parameters:
      deep bool, default=True

        If True, will return the parameters for this estimator and contained subobjects that are estimators.

    Returns:
      params dict

        Parameter names mapped to their values.

  set_params(**params)

    Set the parameters of this estimator.

    The method works on simple estimators as well as on nested objects (such as `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 dict

        Estimator parameters.

    Returns:
      self estimator instance

        Estimator instance.

## Examples using `sklearn.base.BaseEstimator`

Inductive Clustering

Inductive Clustering

__sklearn_is_fitted__ as Developer API

__sklearn_is_fitted__ as Developer API

Metadata Routing

Metadata Routing

Approximate nearest neighbors in TSNE

Approximate nearest neighbors in TSNE