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 ...

Computing the inverse of a matrix is one of the most important operations in machine learning. If some matrix A has shape n-by-n, then its inverse matrix Ai is n-by-n and the matrix product of Ai * A ...

This paper gives a matrix approach to determine when a statistical dependence between two manifest categorical random variables can be viewed as generated by some unobserved latent variables, in the ...