Feature Selection For Machine Learning in Python

Last Updated on August 28, 2020

The data features that you use to train your machine learning models have a huge influence on the performance you can achieve.

Irrelevant or partially relevant features can negatively impact model performance.

In this post you will discover automatic feature selection techniques that you can use to prepare your machine learning data in python with scikit-learn.

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Let’s get started.

  • Update Dec/2016: Fixed a typo in the RFE section regarding the chosen variables.
  • Update Mar/2018: Added alternate link to download the dataset.
  • Update Sep/2019: Fixed code to be compatible with Python 3.
  • Update Dec/2019: Updated univariate selection to use ANOVA.
Feature Selection For Machine Learning in Python

Feature Selection For Machine Learning in Python
Photo by Baptiste Lafontaine, some rights reserved.

Feature Selection

Feature selection is a process where you automatically select those features in your data that contribute most to the prediction variable or output in
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