Article ID Journal Published Year Pages File Type
417299 Computational Statistics & Data Analysis 2008 13 Pages PDF
Abstract

The block or simultaneous clustering problem on a set of objects and a set of variables is embedded in the mixture model. Two algorithms have been developed: block EM as part of the maximum likelihood and fuzzy approaches, and block CEM as part of the classification maximum likelihood approach. A unified framework for obtaining different variants of block EM is proposed. These variants are studied and their performances evaluated in comparison with block CEM, two-way EM and two-way CEM, i.e EM and CEM applied separately to the two sets.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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