An illustration of various linkage option for agglomerative clustering on a 2D embedding of the digits dataset. The goal

class sklearn.feature_selection.SelectFpr(score_func=, alpha=0.05)

Warning DEPRECATED

sklearn.metrics.brier_score_loss(y_true, y_prob, sample_weight=None, pos_label=None)

class sklearn.cluster.AgglomerativeClustering(n_clusters=2, affinity='euclidean', memory=Memory(cachedir=None), connectivity=None

Example of Receiver Operating Characteristic (ROC) metric to evaluate classifier output quality using cross-validation. ROC

class sklearn.naive_bayes.BernoulliNB(alpha=1.0, binarize=0.0, fit_prior=True, class_prior=None)

class sklearn.gaussian_process.kernels.DotProduct(sigma_0=1.0, sigma_0_bounds=(1e-05, 100000.0))

The dataset used in this example is a preprocessed excerpt of the ?Labeled Faces in the Wild?, aka

Warning DEPRECATED