PCA for Classification Is as Bad as Random

Basically, PCA (Principle Component Analysis) finds projection axes based on total population variance. Because that is not correlated with classes, that means that adding PCA into your classification pipeline is essentially adding a random variable. Or, more exactly, it's like using a set of random, orthogonal projection axes. Here's a simple example of PCA making classification harder&hellip;…