Mathematics, Linear Algebra, Machine Learning, Data Science.
correspond to the directions of maximum variance in the data. One criterion, called the “Kaiser criterion” is to keep components whose eigenvalues are greater than 1. Calculating Eigenvalues is also useful when performing Singular Value Decomposition (SVD) Singular Value Decomposition (SVD)