[3dem] clustering algorithms
Morgan, David Gene
dagmorga at indiana.edu
Thu Aug 31 07:24:46 PDT 2017
Hi,
The recent flurry of e-mail about k-means clustering has made me wonder whether anyone in our field has tried to use c-means clustering instead. As I understand it, c-means clustering is an application of "fuzzy logic" to the clustering problem, and another way of describing it (one that might spark a bit more interest) would be to say it merges a clustering algorithm with maximum likelihood: at the end of the process, every particle has a weighted membership in every class. I have no idea whether this would actually be useful for our problems, but I can see some ways that it might be.
So, has anyone tried it, and if so, what are the conclusions? If no-one has tried it, maybe someone will!
Finally, best wishes to our friends in the Houston area.
--
David Gene Morgan
Electron Microscopy Center
047D Simon Hall
IU Bloomington
812 856 1457 (office)
812 856 3221 (3200)
http://iubemcenter.indiana.edu
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