Data Science, Linear Algebra, Dimensionality Reduction, Math.
common way of performing PCA using eigendecomposition. Let’s begin by defining a data matrix X. The dimension of X is “n” by “f”. You could think of it like the data matrix has “n” number of samples and “f” number of features. Before running PCA, it’s always better to center the data, because in