sklearn.metrics.get_scorer(scoring)

sklearn.datasets.make_sparse_coded_signal(n_samples, n_components, n_features, n_nonzero_coefs, random_state=None)

Warning DEPRECATED

sklearn.metrics.consensus_score(a, b, similarity='jaccard')

Principal Component Analysis applied to the Iris dataset. See

A recursive feature elimination example with automatic tuning of the number of features selected with cross-validation.

Partial dependence plots show the dependence between the target function

class sklearn.exceptions.ChangedBehaviorWarning

sklearn.preprocessing.robust_scale(X, axis=0, with_centering=True, with_scaling=True, quantile_range=(25.0, 75.0), copy=True)

class sklearn.multioutput.MultiOutputRegressor(estimator, n_jobs=1)