categoricaldata

<p>It is a categorical data-set simulated using Categorical distribution with 5 modalities. It consist of three clusters in rows and two 
clusters in columns.</p>

datasets

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.

Serge Iovleff

blockcluster

Co-Clustering Package for Binary, Categorical, Contingency and
Continuous Data-Sets

Parmeet Singh Bhatia

Josselin Demont

Vincent Brault

Vincent Kubicki

Gerard Goavert

Christophe Biernacki

Gilles Celeux

categoricaldata function

<p>A data matrix with 1000 rows and 100 columns.</p>

Format

Simulated categorical Data-set — categoricaldata

Simulated categorical Data-set

categoricaldata: Simulated categorical Data-set

Description

Arguments

Format

Examples