sklearn.datasets.make_regression()

sklearn.datasets.make_regression

sklearn.datasets.make_regression(n_samples=100, n_features=100, n_informative=10, n_targets=1, bias=0.0, effective_rank=None, tail_strength=0.5, noise=0.0, shuffle=True, coef=False, random_state=None) [source]

Generate a random regression problem.

The input set can either be well conditioned (by default) or have a low rank-fat tail singular profile. See make_low_rank_matrix for more details.

The output is generated b

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