sklearn.datasets.load_diabetes(return_X_y=False)

sklearn.linear_model.orthogonal_mp(X, y, n_nonzero_coefs=None, tol=None, precompute=False, copy_X=True, return_path=False, r

sklearn.metrics.pairwise.cosine_distances(X, Y=None)

Demonstrate Gradient Boosting on the Boston housing dataset. This example fits a Gradient Boosting model with least squares loss and 500 regression trees

Many statistical problems require at some point the estimation of a population?s covariance matrix, which can be seen as an estimation of data set scatter plot shape.

This example shows how to use cross_val_predict to visualize prediction errors.

class sklearn.cross_decomposition.PLSCanonical(n_components=2, scale=True, algorithm='nipals', max_iter=500, tol=1e-06, copy=True)

The

sklearn.metrics.precision_recall_curve(y_true, probas_pred, pos_label=None, sample_weight=None)

An application of the different