Block clustering with mixture model : Comparison between different
When the data consists of a set of objects described by a set of vari- ables, we have recently proposed a new mixture model which takes into account the block clustering problem on the both sets. In considering this problem under the maximum likelihood and classification maximum likelihood approaches, one can wonder about the performances of the algorithm obtained by block EM, block CEM or by simple uses of the EM and CEM algorithms applied on the both sets separately. The main objective of this paper is to compare these algorithms. Keywords: Block clustering, Mixture model, EM and CEM algorithms.