Christian Roever, Nils Raabe, Karsten Luebke, Uwe Ligges, Gero Szepannek, Marc Zentgraf, David Meyer
scatterplot3d (>= 0.3-22), som, mlbench, rpart, e1071
combinat, questionr, grDevices, stats, utils, graphics
Miscellaneous functions for classification and visualization,
	 e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes, 
	 an interface to 'svmlight' and stepclass() wrapper variable selection 
   	 for supervised classification, partimat() visualization of classification rules 
         and shardsplot() of cluster results as well as kmodes() clustering for categorical data, 
	 corclust() variable clustering, variable extraction from different variable clustering models 
         and weight of evidence preprocessing.