Principal Component Analysis on Big data

Problem Statement Principal component analysis (PCA) is a fairly common statistical technique used to reduce the dimensions¬†of data containing a large set of interrelated variables. Problems start to arise when the number of observations and variables are very large. At this point classical PCA techniques require sizeable memory and immense computational time. While working with … Continue reading Principal Component Analysis on Big data