Package: qcluster 2.0.1

Luca Coraggio

qcluster: Clustering via Quadratic Scoring

Performs tuning of clustering models, methods and algorithms including the problem of determining an appropriate number of clusters. Validation of cluster analysis results is performed via quadratic scoring using resampling methods, as in Coraggio, L. and Coretto, P. (2023) <doi:10.1016/j.jmva.2023.105181>.

Authors:Luca Coraggio [cre, aut], Pietro Coretto [aut]

qcluster_2.0.1.tar.gz
qcluster_2.0.1.tar.gz(r-4.7-arm64)qcluster_2.0.1.tar.gz(r-4.7-x86_64)qcluster_2.0.1.tar.gz(r-4.6-arm64)qcluster_2.0.1.tar.gz(r-4.6-x86_64)
qcluster_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
qcluster/json (API)
NEWS

# Install 'qcluster' in R:
install.packages('qcluster', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
Datasets:

On CRAN:

Conda:

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

openblas

1.30 score 1 scripts 453 downloads 12 exports 5 dependencies

Last updated from:1c82f87bdb. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK110
linux-devel-x86_64OK112
source / vignettesOK166
linux-release-arm64OK113
linux-release-x86_64OK114
wasm-releaseOK102

Exports:bqsbqs_rankbqs_selectclust2paramsgmixmbindmset_gmixmset_kmeansmset_pammset_userplot_clusteringqscore

Dependencies:clustercodetoolsdoParallelforeachiterators