sklearn.ensemble.partial_dependence.plot_partial_dependence(gbrt, X, features, feature_names=None, label=None

This example demonstrates the behavior of Gaussian mixture models fit on data that was not sampled from a mixture of Gaussian random variables. The dataset

class sklearn.multiclass.OneVsOneClassifier(estimator, n_jobs=1)

class sklearn.feature_extraction.text.TfidfTransformer(norm=u'l2', use_idf=True, smooth_idf=True, sublinear_tf=False)

This is an example of applying Non-negative Matrix Factorization and Latent Dirichlet Allocation on a

Warning DEPRECATED

This example compares 2 dimensionality reduction strategies: univariate feature selection with Anova feature

RandomTreesEmbedding provides a way to map data to a very high-dimensional, sparse representation, which might be beneficial for classification

sklearn.cluster.ward_tree(X, connectivity=None, n_clusters=None, return_distance=False)

sklearn.metrics.pairwise.paired_euclidean_distances(X, Y)