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PROBABILISTIC DISTANCE CLUSTERING ADJUSTED FOR CLUSTER SIZE

Published online by Cambridge University Press:  25 September 2008

Cem Iyigun  and
Adi Ben-Israel
Cem Iyigun
Affiliation:
Rutgers Center for Operations Research E-mail: iyigun@business.rutgers.edu
Adi Ben-Israel
Affiliation:
Department of Management Science and Information Systems, School of Business, Rutgers Universityadi.benisrael@gmail.com
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Abstract

The probabilistic distance clustering method of works well if the cluster sizes are approximately equal. We modify that method to deal with clusters of arbitrary size and for problems where the cluster sizes are themselves unknowns that need to be estimated. In the latter case, our method is a viable alternative to the expectation-maximization (EM) method.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 22 , Issue 4 , October 2008 , pp. 603 - 621
Copyright
Copyright © Cambridge University Press 2008

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