Package: supclust 1.1-2

supclust: Supervised Clustering of Predictor Variables Such as Genes

Methodology for supervised grouping aka "clustering" of potentially many predictor variables, such as genes etc, implementing algorithms 'PELORA' and 'WILMA'.

Authors:Marcel Dettling [aut], Martin Maechler [aut, cre]

supclust_1.1-2.tar.gz
supclust_1.1-2.zip(r-4.6)supclust_1.1-2.zip(r-4.5)
supclust_1.1-2.tgz(r-4.6-x86_64)supclust_1.1-2.tgz(r-4.6-arm64)supclust_1.1-2.tgz(r-4.5-x86_64)supclust_1.1-2.tgz(r-4.5-arm64)
supclust_1.1-2.tar.gz(r-4.6-arm64)supclust_1.1-2.tar.gz(r-4.6-x86_64)supclust_1.1-2.tar.gz(r-4.5-arm64)supclust_1.1-2.tar.gz(r-4.5-x86_64)
supclust_1.1-2.tgz(r-4.5-emscripten)
supclust.pdf |supclust.html✨
supclust/json (API)

# Install 'supclust' in R:
install.packages('supclust', repos = c('https://mmaechler.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mmaechler/supclust/issues

Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • leukemia.x - A part of the Golub's famous AML/ALL-leukemia dataset
  • leukemia.y - A part of the Golub's famous AML/ALL-leukemia dataset
  • leukemia.z - A part of the Golub's famous AML/ALL-leukemia dataset

On CRAN:

Conda:

openblas

4.15 score 2 stars 28 scripts 234 downloads 5 mentions 11 exports 3 dependencies

Last updated from:4268e26e82. Checks:12 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK108
linux-devel-x86_64OK106
source / vignettesOK148
linux-release-arm64OK104
linux-release-x86_64OK113
macos-devel-arm64OK90
macos-devel-x86_64OK161
macos-release-arm64OK102
macos-release-x86_64OK230
windows-develOK82
windows-releaseOK83
wasm-releaseOK81

Exports:aggtreesdldalogregmarginnnrpelorascoresign.changesign.flipstandardize.geneswilma

Dependencies:classMASSrpart