[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


More information about the 3dem mailing list