Feature selection

Univariate feature selection

Univariate feature selection works by selecting features based on a univariate test statistic. Although it can seen as a preprocessing step to an estimator, scikit.learn exposes an object to wrap as existing estimator with feature selection and expose a new estimator:

This object takes another estimator, a scoring function that returns univariate p values, and a selection function that selects attributes.

Feature scoring functions

Warning

A common case of non-functionning for feature selection is to use a regression scoring function with a classification problem.

For classification

For regression

Feature selection functions

Examples

Table Of Contents

Previous topic

Artificial Neural Networks

Next topic

Unsupervised learning

This Page