Use Known Groups in High-Dimensional Data to Derive Scores for
Plots
Description
Cross-validated linear discriminant calculations determine
the optimum number of features. Test and training scores from
successive cross-validation steps determine, via a principal
components calculation, a low-dimensional global space onto which test
scores are projected, in order to plot them. Further functions are
included that are intended for didactic use. The package implements,
and extends, methods described in J.H. Maindonald and C.J. Burden (2005)
.