This code was originally written for a course, then extended and used for tutoring in Java and object-oriented programming concepts applied to social science data.
The algorithm for clustering is reasonably easy to describe and code, but non-trivial enough to illustrate import concepts in OO code development.
As an side, the funny name is to distinguish the library from an external "Clustering" library; I simply didn't want name conflicts in my workspace.
Final note: this code, of course, comes with no warranty. See the license file for more information.
To run the test version of the clustering algorithm, do one of the following:
(1) Just run the "testKMeans" main, and then "PlotClusteringOutput.R" in R, or
(2) if you want to play around with the types of possible data speads, open up "MakeSomeData.R" and fiddle around with the data to your hearts desire. Run that file, then run (1) above.
That's all for now...