NORMALLY DISTRIBUTED CLUSTERS is a data generator. It generates a series of random centers for multivariate normal distributions. NDC randomly generates a fraction of data for each center, i.e. what fraction of data points will come from this center. NDC randomly generates a separating plane. Based on this plane, classes for are chosen for each center. NDC then randomly generates the points from the distributions. NDC can increase inseparability by increasng variances of distributions. A measure of "true" separability is obtained by looking at how many points end up on the wrong side of the separating plane. All values are taken as integers for simplicity.

Copyright (C) 1998 David R. Musicant. Version 1.0 This software is free for academic and research use only. For commercial use, contact dmusican@carleton.edu.

The software is free for academic and research use. For commercial use, please contact Dave Musicant.

Click here to download the software, which consists of MATLAB m-files.

If you publish any work based on NDC, please cite both the software and the paper on which it is based. Here is the recommended LaTeX bibliography entries:

@misc{ndc,
author = "D. R. Musicant",
title = {{NDC:} Normally Distributed Clustered Datasets},
year = 1998,
institution = {Computer Sciences Department, University of Wisconsin, Madison},
note = { www.cs.wisc.edu/dmi/svm/ndc/}}