Plot the decision surfaces of forests of randomized trees trained on pairs of features of the iris dataset. This

Example of confusion matrix usage to evaluate the quality of the output of a classifier on the iris data set. The diagonal elements represent the number of points for which

The dataset used in this example is the 20 newsgroups dataset which will be automatically downloaded and then cached and reused for

Computes a Bayesian Ridge Regression on a synthetic dataset. See

The usual covariance maximum likelihood estimate is very sensitive to the presence of outliers in the data set. In such a case, it would be better to

Lasso and elastic net (L1 and L2 penalisation) implemented using a coordinate descent. The coefficients can be forced to be positive.

The following example illustrates the effect of scaling the regularization parameter when using

This example constructs a pipeline that does dimensionality reduction followed by prediction with a support vector classifier

Both kernel ridge regression (KRR) and SVR learn a non-linear function by employing the kernel trick, i.e., they learn a linear function in the

An illustration of the isotonic regression on generated data. The isotonic regression finds a non-decreasing approximation of a function while minimizing the mean squared