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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: Clustering results


Reference manual: Clustering.pdf


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


Please use the canonical form to link to this page.