Feature Selection Basics

2.7.1

Feature Selection Basics

Last updated 2020-01-29 Read time 1 min
Summary

  • Feature selection keeps only the truly useful features from a large set. Removing irrelevant features helps prevent overfitting, speed...

  • model assumptions and when the method is appropriate.
  • objective criteria and how they influence model behavior.

Intuition #

Feature selection keeps only the truly useful features from a large set. Removing irrelevant features helps prevent overfitting, speeds up training, and improves interpretability.

Detailed Explanation #

Feature selection keeps only the truly useful features from a large set. Removing irrelevant features helps prevent overfitting, speeds up training, and improves interpretability.