Transform your features into a higher dimensional, sparse space. Then train a linear model on these features. First fit an ensemble of

This data sets consists of 3 different types of irises? (Setosa, Versicolour, and Virginica) petal and sepal length, stored in a 150x4 numpy.ndarray The rows being the

This examples shows how a classifier is optimized by cross-validation, which is done using the

Use the Akaike information criterion (AIC), the Bayes Information criterion (BIC) and cross-validation to select an optimal value of the regularization

A tutorial exercise for using different SVM kernels. This exercise is used in the

This example illustrates visually in the feature space a comparison by results using two different component analysis techniques.

Plot the density estimation of a mixture of two Gaussians. Data is generated from two Gaussians with different centers and covariance matrices.

This example shows the use of multi-output estimator to complete images. The goal is to predict the lower half of a face given its upper half

In many real-world examples, there are many ways to extract features from a dataset. Often it is beneficial to combine several methods to obtain

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