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scikit-learn 1.3.2
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# `sklearn.utils`.check_random_state

sklearn.utils.check_random_state(seed)

  Turn seed into a np.random.RandomState instance.

  Parameters:
    seed None, int or instance of RandomState

      If seed is None, return the RandomState singleton used by np.random. If seed is an int, return a new RandomState instance seeded with seed. If seed is already a RandomState instance, return it. Otherwise raise ValueError.

  Returns:
    `numpy.random.RandomState`

      The random state object based on `seed` parameter.

## Examples using `sklearn.utils.check_random_state`

Empirical evaluation of the impact of k-means initialization

Empirical evaluation of the impact of k-means initialization

MNIST classification using multinomial logistic + L1

MNIST classification using multinomial logistic + L1

Manifold Learning methods on a severed sphere

Manifold Learning methods on a severed sphere

Face completion with a multi-output estimators

Face completion with a multi-output estimators

Isotonic Regression

Isotonic Regression