hddplot: Use Known Groups in High-Dimensional Data to Derive Scores for Plots

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) <https://journal.austms.org.au/V46/CTAC2004/Main/home.html>.

install.packages("hddplot")

Try the hddplot package in your browser