sklearn.datasets.mldata_filename(dataname)

This example illustrates the predicted probability of GPC for an RBF kernel with different choices of the hyperparameters

class sklearn.preprocessing.Normalizer(norm='l2', copy=True)

sklearn.feature_extraction.image.img_to_graph(img, mask=None, return_as=, dtype=None)

class sklearn.svm.SVC(C=1.0, kernel='rbf', degree=3, gamma='auto', coef0=0.0, shrinking=True, probability=False, tol=0.001, cache_size=200, class_weight=None

sklearn.metrics.fowlkes_mallows_score(labels_true, labels_pred, sparse=False)

Shown in the plot is how the logistic regression would, in this synthetic dataset, classify values as either 0 or 1, i.e. class one or two, using the logistic curve.

class sklearn.feature_extraction.DictVectorizer(dtype=, separator='=', sparse=True, sort=True)

Warning DEPRECATED class sklearn

This example compares the timing of Birch (with and without the global clustering step) and MiniBatchKMeans on a synthetic dataset having 100,000 samples and