Wrapper Based Feature Selection Techniques

There are many ways in which features can be selected from a set of predictors to improve the performance of the machine learning models. Among these techniques, a common practice is used to use another machine learning model as a wrapper, trained on the set of predictor combinations to determine which set of predictors performs the best on the given model.

In this article we shall look into some of the popular machine learning algorithms such as Recursive Feature Elimination (RFE), Forward Feature Selection, and Backward Feature Elimination. Since this…