Package: CrossClustering 4.1.3

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_4.1.3.tar.gz
CrossClustering_4.1.3.zip(r-4.7-any)CrossClustering_4.1.3.zip(r-4.6-any)CrossClustering_4.1.3.zip(r-4.5-any)
CrossClustering_4.1.3.tgz(r-4.6-any)CrossClustering_4.1.3.tgz(r-4.5-any)
CrossClustering_4.1.3.tar.gz(r-4.7-any)CrossClustering_4.1.3.tar.gz(r-4.6-any)
CrossClustering_4.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
CrossClustering/json (API)

# Install 'CrossClustering' in R:

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

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:

3.41 score 1 stars 52 scripts 449 downloads 9 exports 32 dependencies

Last updated from:15388f7f3e. Checks:2 NOTE, 7 OK. Indexed: yes.

Target	Result	Time
linux-devel	NOTE	136
source / vignettes	OK	175
linux-release	OK	132
macos-release	OK	169
macos-oldrel	OK	204
windows-devel	NOTE	88
windows-release	OK	75
windows-oldrel	OK	85
wasm-release	OK	113

Exports:ari cc_crossclustering cc_get_cluster cc_test_ari cc_test_ari_permutation consensus_cluster is_zero prune_zero_tail reverse_table

Dependencies:backports bitops checkmate cherry class cli cluster crayon dplyr e1071 flip generics glue hommel lifecycle lpSolve magrittr mclust pillar pkgconfig plyr proxy purrr R6 Rcpp rlang someMTP tibble tidyselect utf8 vctrs withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Computes the adjusted Rand index and the confidence interval, comparing two classifications from a contingency table.	ari print.ari
A partial clustering algorithm with automatic estimation of the number of clusters and identification of outliers	cc_crossclustering print.crossclustering
Provides the vector of clusters' ID to which each element belong to.	cc_get_cluster cc_get_cluster.crossclustering cc_get_cluster.default
A test for testing the null hypothesis of random agreement (i.e., adjusted Rand Index equal to 0) between two partitions.	cc_test_ari
A permutation test for testing the null hypothesis of random agreement (i.e., adjusted Rand Index equal to 0) between two partitions.	cc_test_ari_permutation
A toy dataset for illustrating the chain effect.	chain_effect
Get clusters which reach max consensus	consensus_cluster
Check for zero	is_zero
RNA-Seq dataset example	nb_data
Prune tail made of zeros	prune_zero_tail
Reverse the process of create a contingency table	reverse_table
A toy example matrix	toy
A famous shape data set containing two clusters with two moons shapes and outliers	twomoons
A famous shape data set containing two clusters with two worms shapes and outliers	worms