XEMStrategy

In Co-clustering, there could be many local optimal where
  the algorithm may get struck 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, continuous and categorical
    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. More
    information about the project and comprehensive tutorial can be found on
    the link mentioned in URL.

XEMStrategy: An EM strategy to obtain a good optimum.

Description

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