Linear Discriminant Analysis

I received a lot of positive feedback about the step-wise Principal Component Analysis (PCA) implementation. Thus, I decided to write a little follow-up about Linear Discriminant Analysis (LDA) — another useful linear transformation technique. Both LDA and PCA are commonly used dimensionality reduction techniques in statistics, pattern classification, and machine learning applications. By implementing the LDA step-by-step in Python, we will see and understand how it works, and we will compare it to a PCA to see how it differs.