Principal component analysis is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. This book reduces to the solution of an eigenvalue eigenvector problem for a positive semi definite symmetric matrix.
Print ISBN: 9781682502556 | $ 170 | 2016 | Hardcover
Contributors: Maria Monfreda et al