sklearn.covariance.ledoit_wolf(X, assume_centered=False, block_size=1000)

class sklearn.feature_selection.SelectKBest(score_func=, k=10)

This example demonstrates the problems of underfitting and overfitting and how we can use linear regression with polynomial features to approximate nonlinear functions

sklearn.datasets.fetch_lfw_people(data_home=None, funneled=True, resize=0.5, min_faces_per_person=0, color=False, slice_=(slice(70

This example plots the ellipsoids obtained from a toy dataset (mixture of three Gaussians) fitted by the Baye

sklearn.metrics.silhouette_score(X, labels, metric='euclidean', sample_size=None, random_state=None, **kwds)

Demonstrates an active learning technique to learn handwritten digits using label propagation. We start by training a label propagation model

sklearn.metrics.homogeneity_completeness_v_measure(labels_true, labels_pred)

class sklearn.linear_model.OrthogonalMatchingPursuitCV(copy=True, fit_intercept=True, normalize=True, max_iter=None

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