class sklearn.model_selection.LeaveOneGroupOut

sklearn.metrics.coverage_error(y_true, y_score, sample_weight=None)

class sklearn.base.BaseEstimator

class sklearn.model_selection.GridSearchCV(estimator, param_grid, scoring=None, fit_params=None, n_jobs=1, iid=True, refit=True

sklearn.model_selection.cross_val_score(estimator, X, y=None, groups=None, scoring=None, cv=None, n_jobs=1, verbose=0, fit_params=None

This example illustrates the predicted probability of GPC for an isotropic and anisotropic RBF kernel on a two-dimensional version for the

An introduction to machine learning

Example builds a swiss roll dataset and runs hierarchical clustering on their position. For more information, see

An illustration of Swiss Roll reduction with locally linear embedding

The sklearn