aricode: Efficient Computations of Standard Clustering Comparison Measures

Implements an efficient O(n) algorithm based on bucket-sorting for fast computation of standard clustering comparison measures. Available measures include adjusted Rand index (ARI), normalized information distance (NID), normalized mutual information (NMI), adjusted mutual information (AMI), normalized variation information (NVI) and entropy, as described in Vinh et al (2009) <doi:10.1145/1553374.1553511>. Include AMI (Adjusted Mutual Information) since version 0.1.2, a modified version of ARI (MARI), as described in Sundqvist et al. <doi:10.1007/s00180-022-01230-7> and simple Chi-square distance since version 1.0.0.

Version: 1.0.3
Imports: Matrix, Rcpp
LinkingTo: Rcpp
Suggests: testthat, spelling
Published: 2023年10月20日
Author: Julien Chiquet ORCID iD [aut, cre], Guillem Rigaill [aut], Martina Sundqvist [aut], Valentin Dervieux [ctb], Florent Bersani [ctb]
Maintainer: Julien Chiquet <julien.chiquet at inrae.fr>
License: GPL (≥ 3)
NeedsCompilation: yes
Language: en-US
Materials: NEWS
CRAN checks: aricode results

Documentation:

Reference manual: aricode.html , aricode.pdf

Downloads:

Package source: aricode_1.0.3.tar.gz
Windows binaries: r-devel: aricode_1.0.3.zip, r-release: aricode_1.0.3.zip, r-oldrel: aricode_1.0.3.zip
macOS binaries: r-release (arm64): aricode_1.0.3.tgz, r-oldrel (arm64): aricode_1.0.3.tgz, r-release (x86_64): aricode_1.0.3.tgz, r-oldrel (x86_64): aricode_1.0.3.tgz
Old sources: aricode archive

Reverse dependencies:

Reverse suggests: clustSIGNAL, FCPS, FisherEM, missSBM, sbm

Linking:

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