Numerical evaluation of cytologic data. VIII. Computation of the principal components

The principal components transformation offers an effective methods for dimensionality reduction and for the assessment of the mutual dependence of observed variables in a data set. An iterative procedure, the so-called power method, for finding a multivariate distribution's eigenvectors and eigenvalues is demonstrated. The projection of feature vectors onto the principal components is shown.