Principal components are the directions in which the input data have the largest variances.
Expressing data vectors in terms of the principal components is called Principal Component
Analysis (PCA). On the Other hand, the minor components are the directions in which the
data have the smallest variances. Minor Component Analysis (MCA), counterpart of PCA,
and principal component analysis, are powerful statistical techniques for analy...