Simple usage of Pipeline that runs successively a univariate feature selection with anova and then a C-SVM of the selected features.

A recursive feature elimination example with automatic tuning of the number of features selected with cross-validation.

In order to test if a classification score is significative a technique in repeating the classification procedure after randomizing

Use SelectFromModel meta-transformer along with Lasso to select the best couple of features from the Boston dataset.

This example illustrates the differences between univariate F-test statistics and mutual information. We consider 3 features x_1, x_2, x_3

An example showing univariate feature selection. Noisy (non informative) features are added to the iris data and univariate feature selection is applied

A recursive feature elimination example showing the relevance of pixels in a digit classification task.