XEMStrategy

In co-clustering, there could be many local optima where
  the algorithm may get struct resulting in sub-optimum
  results. Hence we applied a strategy called XEM strategy
  to run the EM algorithm. The various steps are defined as
  follows:

Simultaneous clustering of rows and columns, usually
        designated by biclustering, co-clustering or block clustering,
        is an important technique in two way data analysis. It consists
        of estimating a mixture model which takes into account the
        block clustering problem on both the individual and variables
        sets. The blockcluster package provides a bridge between the
        C++ core library and the R statistical computing environment.
        This package allows to co-cluster Binary, contingency and
        continuous data-sets. It also provides utility functions to
        visualize the results. This package may be useful for various
        applications in fields of Data mining,Information retrieval,
        Biology, computer vision and many more.

XEMStrategy: An EM strategy to obtain a good optimum.

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