XEMStrategy

<p>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:</p>

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 build on top of the 'STK++' library, and the R statistical
computing environment. This package allows to co-cluster binary
<doi:10.1016/j.csda.2007.09.007>, contingency <doi:10.1080/03610920903140197>,
continuous <doi:10.1007/s11634-013-0161-3> and categorical data-sets
<doi:10.1007/s11222-014-9472-2>. 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

Arguments

Details