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: | 1.7.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | advclust, amap, apcluster, cluster, ClusterR, data.table, doParallel, dplyr, foreach, future, gama, ggplot2, gmp, pracma, pvclust, shiny, sqldf, stats, tools, utils, xtable |
| Suggests: | DT, kableExtra, knitr, rmarkdown, shinyalert, shinyFiles, shinyjs, shinythemes, shinyWidgets, tidyverse, shinycssloaders |
| Published: | 2020-12-04 |
| 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 |
| Reference manual: | Clustering.pdf |
| Vignettes: |
Techniques for Evaluating Clustering Data in R. The **Clustering** Package |
| Package source: | Clustering_1.7.1.tar.gz |
| Windows binaries: | r-devel: Clustering_1.7.1.zip, r-release: Clustering_1.7.1.zip, r-oldrel: Clustering_1.7.1.zip |
| macOS binaries: | r-release: Clustering_1.7.1.tgz, r-oldrel: Clustering_1.7.1.tgz |
| Old sources: | Clustering archive |
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