Applied Linear Algebra Methods for Data Science
Chien Hsu, Jin Wang · 2019
In this paper, we discuss efficient algorithms for using eigenvalues and eigenvectors. The main algorithm is t Principal Component Analysis (PCA), a powerful method widely used for dimensionality reduction, image compression, and face recognition. We derive the optimal k of the number of principal components selected. The implementation of PCA application is demonstrated by an image compression example using the MATLAB programming language. We also discuss PageRank and Network Classification algorithms.