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-4.5)supclust_1.1-2.zip(r-4.4)supclust_1.1-2.zip(r-4.3)
supclust_1.1-2.tgz(r-4.4-x86_64)supclust_1.1-2.tgz(r-4.4-arm64)supclust_1.1-2.tgz(r-4.3-x86_64)supclust_1.1-2.tgz(r-4.3-arm64)
supclust_1.1-2.tar.gz(r-4.5-noble)supclust_1.1-2.tar.gz(r-4.4-noble)
supclust_1.1-2.tgz(r-4.4-emscripten)supclust_1.1-2.tgz(r-4.3-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'))

Peer review:

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:

11 exports 2 stars 1.92 score 3 dependencies 5 mentions 28 scripts 267 downloads

Last updated 1 months agofrom:4268e26e82. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-win-x86_64OKSep 13 2024
R-4.5-linux-x86_64OKSep 13 2024
R-4.4-win-x86_64OKSep 13 2024
R-4.4-mac-x86_64OKSep 13 2024
R-4.4-mac-aarch64OKSep 13 2024
R-4.3-win-x86_64OKSep 13 2024
R-4.3-mac-x86_64OKSep 13 2024
R-4.3-mac-aarch64OKSep 13 2024

Exports:aggtreesdldalogregmarginnnrpelorascoresign.changesign.flipstandardize.geneswilma

Dependencies:classMASSrpart