Package: EnsCat 1.1

Saeid Amiri

EnsCat: Clustering of Categorical Data

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 <arxiv:1506.07930>.

Authors:Saeid Amiri, Bertrand Clarke and Jennifer Clarke.

EnsCat_1.1.tar.gz
EnsCat_1.1.zip(r-4.7-any)EnsCat_1.1.zip(r-4.6-any)EnsCat_1.1.zip(r-4.5-any)
EnsCat_1.1.tgz(r-4.6-any)EnsCat_1.1.tgz(r-4.5-any)
EnsCat_1.1.tar.gz(r-4.7-any)EnsCat_1.1.tar.gz(r-4.6-any)
EnsCat_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
EnsCat/json (API)

# Install 'EnsCat' in R:
install.packages('EnsCat', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Datasets:
  • alphadata - Alphaherpesvirinae virus genome sequence data
  • cancer - Primary tumor domain (cancer) data
  • ebola - Ebolavirus genome sequence data
  • lympho - Lymphography domian (lympho) data
  • mush - Mushroom data
  • rhabdodata - Rhabdoviridae virus genome sequence data
  • soybean - Soybean (small) data
  • USFlag - United States Flag Privately-Owned Merchant Fleet Data
  • zoo - Zoo data

On CRAN:

Conda:

archivedpackagesr-universe

2.04 score 5 stars 22 scripts 334 downloads 1 mentions 7 exports 32 dependencies

Last updated from:b7d385ed57 (on package/EnsCat). Checks:7 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develNOTE128
source / vignettesOK172
linux-releaseNOTE133
macos-releaseNOTE122
macos-oldrelNOTE133
windows-develNOTE113
windows-releaseNOTE111
windows-oldrelNOTE97
wasm-releaseOK89

Exports:BenhcCTNenhcHiggdplothammingDkmodestangle

Dependencies:ade4clicpp11dendextendfarverggdendroggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSnlmepixmapR6RColorBrewerRcppRcppArmadillorlangS7scalessegmentedseqinrspvctrsviridisviridisLitewithr