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

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

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

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

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

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

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