Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
417299 | Computational Statistics & Data Analysis | 2008 | 13 Pages |
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
Authors
Gérard Govaert, Mohamed Nadif,