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

Arguments

Details