Package: WOAkMedoids 0.2.2

Chenan Huang

WOAkMedoids: Whale Optimization Algorithm for K-Medoids Clustering

Implements the Whale Optimization Algorithm(WOA) for k-medoids clustering, providing tools for effective and efficient cluster analysis in various data sets. The methodology is based on "The Whale Optimization Algorithm" by Mirjalili and Lewis (2016) <doi:10.1016/j.advengsoft.2016.01.008>.

Authors:Chenan Huang [aut, cre], Narumasa Tsutsumida [aut]

WOAkMedoids_0.2.2.tar.gz
WOAkMedoids_0.2.2.tar.gz(r-4.7-arm64)WOAkMedoids_0.2.2.tar.gz(r-4.7-x86_64)WOAkMedoids_0.2.2.tar.gz(r-4.6-arm64)WOAkMedoids_0.2.2.tar.gz(r-4.6-x86_64)
WOAkMedoids_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
WOAkMedoids/json (API)

# Install 'WOAkMedoids' in R:
install.packages('WOAkMedoids', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.00 score 157 downloads 1 exports 73 dependencies

Last updated from:29fa7ddf76. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK178
linux-devel-x86_64OK163
source / vignettesOK175
linux-release-arm64OK178
linux-release-x86_64OK165
wasm-releaseOK124

Exports:woa_kmedoids

Dependencies:base64encbslibcachemclasscliclueclustercodetoolscommonmarkcpp11digestdplyrdtwdtwclustfarverfastmapflexclustfontawesomeforeachfsgenericsggplot2ggrepelgluegtablehtmltoolshttpuvisobanditeratorsjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemimemodeltoolsotelpillarpkgconfigplyrpromisesproxyR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcppThreadreshape2rlangRSpectraS7sassscalesshinyshinyjssourcetoolsstringistringrtibbletidyselectutf8vctrsviridisLitewithrxtable