Clustering: Techniques for Evaluating Clustering

The design of this package allows us to run different clustering packages and compare the results between them, to determine which algorithm behaves best from the data provided.

Version: 1.7.7
Depends: R (≥ 3.5.0)
Imports: amap, apcluster, cluster, ClusterR, data.table, doParallel, dplyr, foreach, future, ggplot2, gmp, methods, pracma, pvclust, shiny, sqldf, stats, tools, utils, xtable, toOrdinal
Suggests: DT, shinyalert, shinyFiles, shinyjs, shinythemes, shinyWidgets, tidyverse, shinycssloaders
Published: 2022-06-22
Author: Luis Alfonso Perez Martos [aut, cre]
Maintainer: Luis Alfonso Perez Martos <lapm0001 at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/laperez/clustering
NeedsCompilation: no
CRAN checks: Clustering results

Documentation:

Reference manual: Clustering.pdf

Downloads:

Package source: Clustering_1.7.7.tar.gz
Windows binaries: r-devel: Clustering_1.7.7.zip, r-release: Clustering_1.7.7.zip, r-oldrel: Clustering_1.7.7.zip
macOS binaries: r-release (arm64): Clustering_1.7.7.tgz, r-oldrel (arm64): Clustering_1.7.7.tgz, r-release (x86_64): Clustering_1.7.7.tgz
Old sources: Clustering archive

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