The command runs the k-means clustering algorithm to divide data into k numbers of clusters. The centroids of the clusters are stored into the frame <data> and the classification information between clusters and data records into the classified data <cldata>.
Example (ex5.15): In the example, the Boston data is divided into five clusters which are visualized through their centroids.
... NDA> load boston.dat NDA> select flds -f boston.indus boston.age boston.zn boston.dis NDA> kmeans -d flds -dout clusdat -cout cluscld -k 5 # NDA> mkgrp win1 -d clusdat ...
