KlustaKwik is a program for unsupervised classification of multidimensional
continuous data. It arose from a specific need – automatic sorting of neuronal
action potential waveforms (see here), but works for any type of data.


The program can:
1) Fit a mixture of Gaussians with unconstrained covariance matrices
2) Automatically choose the number of mixture components
3) Be robust against noise
4) Reduce the problem of local minima
5) Run fast on large data sets (up to 100000 points, 48 dimensions)
KlustaKwik is based on the CEM algorithm of Celeux and Govaert (which is faster than the standard EM algorithm), and also uses several tricks to improve execution speed while maintaining good performance.
Visit Klustakwik’s Home Page
This program is copyright Ken Harris (harris@axon.rutgers.edu), 2000-2002. It
is distributed under the GNU General Public License (www.gnu.org)

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