Mastering Machine Learning with R - Second Edition

Feature Selection with random forests

So far, we've looked at several feature selection techniques, such as regularization, best subsets, and recursive feature elimination. I now want to introduce an effective feature selection method for classification problems with Random Forests using the Boruta package. A paper is available that provides details on how it works in providing all relevant features:

Kursa M., Rudnicki W. (2010), Feature Selection with the Boruta Package, Journal of Statistical Software, 36(11), 1 - 13

What I will do here is provide an overview of the algorithm and then apply it to a wide dataset. This will not serve as a separate business case but as a template to apply the methodology. I have found it to be highly effective, ...