Package: CrossClustering 4.1.2

Paola Tellaroli

CrossClustering: A Partial Clustering Algorithm

Provide the 'CrossClustering' algorithm (Tellaroli et al. (2016) <doi:10.1371/journal.pone.0152333>), which is a partial clustering algorithm that combines the Ward's minimum variance and Complete Linkage algorithms, providing automatic estimation of a suitable number of clusters and identification of outlier elements.

Authors:Paola Tellaroli [cre, aut], Marco Bazzi [aut], Michele Donato [aut], Livio Finos [aut], Philippe Courcoux [aut], Corrado Lanera [aut]

CrossClustering_4.1.2.tar.gz
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CrossClustering.pdf |CrossClustering.html
CrossClustering/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/corradolanera/crossclustering/issues

Datasets:
  • chain_effect - A toy dataset for illustrating the chain effect.
  • nb_data - RNA-Seq dataset example
  • toy - A toy example matrix
  • twomoons - A famous shape data set containing two clusters with two moons shapes and outliers
  • worms - A famous shape data set containing two clusters with two worms shapes and outliers

On CRAN:

9 exports 1 stars 1.01 score 34 dependencies 39 scripts 168 downloads

Last updated 4 months agofrom:20821e2455. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 05 2024
R-4.5-winOKSep 05 2024
R-4.5-linuxOKSep 05 2024
R-4.4-winOKSep 05 2024
R-4.4-macOKSep 05 2024
R-4.3-winOKSep 05 2024
R-4.3-macOKSep 05 2024

Exports:aricc_crossclusteringcc_get_clustercc_test_aricc_test_ari_permutationconsensus_clusteris_zeroprune_zero_tailreverse_table

Dependencies:backportsbitopscheckmatecherryclasscliclustercrayondplyre1071fansiflipgenericsgluehommellifecyclelpSolvemagrittrMASSmclustpillarpkgconfigplyrproxypurrrR6RcpprlangsomeMTPtibbletidyselectutf8vctrswithr