Singular Value Decomposition (SVD) factors a real matrix into three specific matrices, providing a method for dimensionality reduction. While similar to Principal Component Analysis (PCA), SVD operates directly on the data matrix rather than the covariance matrix.
HOW THIS AFFECTS YOU
●
researcherThis serves as a fundamental mathematical refresher for dimensionality reduction techniques.