Principal Components Analysis (PCA)
PCA Machine Learning
PCA or Principal Component Analysis is one of the most powerful techniques of dimension reduction. Although this is a statistical technique, yet heavily used in Machine Learning model development. If a dataset has a high number of features/ columns/ dimensions, then PCA can compress that information into a couple of PC (principal components) and then we can use these columns to develop models. In this article, I am trying to explain how it works.