Package com.numericalmethod.suanshu.stats.pca

Interface Summary

Interface	Description
PCA	Principal Component Analysis (PCA) is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables called principal components.

Class Summary

Class	Description
PCAbyEigen	This class performs a principal component analysis (PCA) on the given data matrix.
PCAbySVD	This class performs a Principal Component Analysis (PCA) on the given data matrix using the preferred singular value decomposition (SVD) method.