Principal Component Analysis from Scratch Using Singular Value Decomposition with C#. Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

I. T. Jolliffe, Discarding Variables in a Principal Component Analysis. I: Artificial Data, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 21, No. 2 (1972), pp. 160-173.

Principal component analysis (PCA) simplifies the complexity in high-dimensional data while retaining trends and patterns. It does this by transforming the data into fewer dimensions, which act as ...