EnsCat (version 1.1)

Clustering of Categorical Data

Description

An implementation of the clustering methods of categorical data discussed in Amiri, S., Clarke, B., and Clarke, J. (2015). Clustering categorical data via ensembling dissimilarity matrices. Preprint .

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Version

Install

install.packages('EnsCat')

Monthly Downloads

173

Version

1.1

License

GPL (>= 2)

Maintainer

Saeid Amiri

Last Published

January 31st, 2017

Functions in EnsCat (1.1)

ggdplot

Nice plots of hierarchical clustering results via ggdendrogram

enhcHi

Performs ensemble hierarchical clustering for high dimensional categorical data

kmodes

Run Kmodes

ebola

Ebolavirus genome sequence data

alphadata

Alphaherpesvirinae virus genome sequence data

CTN

convert genetic data (nucleotides) to numerical values

zoo

zoo data

tangle

Generate a tanglegram from two hierarchical clusterings of a data set

USFlag

United States Flag Privately-Owned Merchant Fleet Data

lympho

Lymphography domian (lympho) data

soybean

Soybean (small) data

rhabdodata

Rhabdoviridae virus genome sequence data

mush

Mushroom data

EnsCat

This package includes several methods that can be used to cluster categorical data.

hammingD

Calculate the hamming distance between data points.

Benhc

Performs bootstrap ensemble hierarchical clustering for categorical data.

cancer

Primary tumor domain (cancer) data