Feature Selection: Beyond feature importance? - KDnuggets

In machine learning, Feature Selection is the process of choosing features that are most useful for your prediction. Although it sounds simple it is one of the most complex problems in the work of creating a new machine learning model. In this post, I will share with you some of the approaches that were researched during the last project I led at Fiverr. You will get some ideas on the basic method I tried and also the more complex approach, which got the best results -- removing over 60% of the features, while maintaining accuracy and achieving more stability for our model. I'll also be sharing our improvement to this algorithm.