Package: qVarSel 1.2

qVarSel: Select Variables for Optimal Clustering

Finding hidden clusters in structured data can be hindered by the presence of masking variables. If not detected, masking variables are used to calculate the overall similarities between units, and therefore the cluster attribution is more imprecise. The algorithm q-vars implements an optimization method to find the variables that most separate units between clusters. In this way, masking variables can be discarded from the data frame and the clustering is more accurate. Tests can be found in Benati et al.(2017) <doi:10.1080/01605682.2017.1398206>.

Authors:Stefano Benati [aut, cre]

qVarSel_1.2.tar.gz
qVarSel_1.2.zip(r-4.7)qVarSel_1.2.zip(r-4.6)qVarSel_1.2.zip(r-4.5)
qVarSel_1.2.tgz(r-4.6-x86_64)qVarSel_1.2.tgz(r-4.6-arm64)qVarSel_1.2.tgz(r-4.5-x86_64)qVarSel_1.2.tgz(r-4.5-arm64)
qVarSel_1.2.tar.gz(r-4.7-arm64)qVarSel_1.2.tar.gz(r-4.7-x86_64)qVarSel_1.2.tar.gz(r-4.6-arm64)qVarSel_1.2.tar.gz(r-4.6-x86_64)
qVarSel_1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
qVarSel/json (API)

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

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 4 scripts 541 downloads 3 exports 2 dependencies

Last updated from:8dd9c3ac64. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK140
linux-devel-x86_64OK105
source / vignettesOK160
linux-release-arm64OK131
linux-release-x86_64OK110
macos-release-arm64OK155
macos-release-x86_64OK323
macos-oldrel-arm64OK170
macos-oldrel-x86_64OK238
windows-develOK106
windows-releaseOK85
windows-oldrelOK89
wasm-releaseOK109

Exports:PrtDistqVarSelHqVarSelLP

Dependencies:lpSolveAPIRcpp