sklearn.base.MetaEstimatorMixin

class sklearn.base.MetaEstimatorMixin

Mixin class for all meta estimators in scikit-learn.

This mixin defines the following functionality:

• define _required_parameters that specify the mandatory estimator parameter.

Examples

>>> from sklearn.base import MetaEstimatorMixin
>>> from sklearn.datasets import load_iris
>>> from sklearn.linear_model import LogisticRegression
>>> class MyEstimator(MetaEstimatorMixin):
...     def __init__(self, *, estimator=None):
...         self.estimator = estimator
...     def fit(self, X, y=None):
...         if self.estimator is None:
...             self.estimator_ = LogisticRegression()
...         else:
...             self.estimator_ = self.estimator
...         return self
>>> X, y = load_iris(return_X_y=True)
>>> estimator = MyEstimator().fit(X, y)
>>> estimator.estimator_
LogisticRegression()

Examples using sklearn.base.MetaEstimatorMixin

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