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blockcluster (version 3.0.2)

Coclustering package for binary, contingency, continuous and categorical data-sets

Description

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.

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Version

Install

install.packages('blockcluster')

Monthly Downloads

373

Version

3.0.2

License

GPL (>= 3)

Maintainer

Vincent KUBICKI

Last Published

January 23rd, 2015

Functions in blockcluster (3.0.2)

cocluster

Co-Clustering function.
contingencydatalist

Simulated Contingency Data-set
XEMStrategy

An EM strategy to obtain a good optimum.
CategoricalOptions-class

Categorical input/output options
contingencydataunknown

Simulated Contingency Data-set
strategy-class

strategy class
blockcluster

Co-Clustering Package
BinaryOptions-class

Binary input/output options
[

Getter method for Rcoclust output
gaussiandata

Simulated Gaussian Data-set
cocluststrategy

Strategy function
ContinuousOptions-class

Continuous input/output options
ContingencyOptions-class

Contingency input/output options
summary

Summary function.
plot

Plot function.
categoricaldata

Simulated categorical Data-set
binarydata

Simulated Binary Data-set
CommonOptions-class

Common Input/Output options.