Package: supclust 1.1-1

Martin Maechler

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 <[email protected]> and Martin Maechler

supclust_1.1-1.tar.gz
supclust_1.1-1.tar.gz(r-4.7-arm64)supclust_1.1-1.tar.gz(r-4.7-x86_64)supclust_1.1-1.tar.gz(r-4.6-arm64)supclust_1.1-1.tar.gz(r-4.6-x86_64)
supclust_1.1-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
supclust/json (API)

# Install 'supclust' in R:
install.packages('supclust', repos = c('https://cran.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

2.85 score 28 scripts 223 downloads 5 mentions 11 exports 3 dependencies

Last updated from:2bfe21d479. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK112
linux-devel-x86_64OK106
source / vignettesOK163
linux-release-arm64OK121
linux-release-x86_64OK101
wasm-releaseOK103

Exports:aggtreesdldalogregmarginnnrpelorascoresign.changesign.flipstandardize.geneswilma

Dependencies:classMASSrpart