OTclust: Mean Partition, Uncertainty Assessment, Cluster Validation and Visualization Selection for Cluster Analysis

Providing mean partition for ensemble clustering by optimal transport alignment(OTA), uncertainty measures for both partition-wise and cluster-wise assessment and multiple visualization functions to show uncertainty, for instance, membership heat map and plot of covering point set. A partition refers to an overall clustering result. Jia Li, Beomseok Seo, and Lin Lin (2019) <doi:10.1002/sam.11418>. Lixiang Zhang, Lin Lin, and Jia Li (2020) <doi:10.1093/bioinformatics/btaa165>.

Version: 1.0.6
Depends: R (≥ 3.5.0)
Imports: Rcpp, ggplot2, RColorBrewer, magrittr, class
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, tsne, umap, HDclust, dbscan, flexclust, mclust
Published: 2023-10-06
Author: Lixiang Zhang [aut, cre], Beomseok Seo [aut], Lin Lin [aut], Jia Li [aut]
Maintainer: Lixiang Zhang <phoelief at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: OTclust results

Documentation:

Reference manual: OTclust.pdf
Vignettes: Quick tour of OTclust

Downloads:

Package source: OTclust_1.0.6.tar.gz
Windows binaries: r-devel: OTclust_1.0.6.zip, r-release: OTclust_1.0.6.zip, r-oldrel: OTclust_1.0.6.zip
macOS binaries: r-release (arm64): OTclust_1.0.6.tgz, r-oldrel (arm64): OTclust_1.0.6.tgz, r-release (x86_64): OTclust_1.0.6.tgz
Old sources: OTclust archive

Linking:

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