AI, Dimensionality Reduction, Machine Learning, Python, Data Science.
Matrix Given a matrix M of size m x n (or a data frame with m rows and n columns), SVD decomposes it into three matrices: M = U *Σ *Vᵗ, where U is an m x m orthogonal matrix, Σ is an m x r diagonal matrix, and V is an r x n orthogonal matrix. r is the rank of the matrix M. The diagonal elements of