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) and simple Chi-square distance since version 1.0.0.

Version: 1.0.0
Imports: Matrix, Rcpp
LinkingTo: Rcpp
Suggests: testthat, spelling
Published: 2020-06-26
Author: Julien Chiquet ORCID iD [aut, cre], Guillem Rigaill [aut], Martina Sundqvist [aut], Valentin Dervieux [ctb]
Maintainer: Julien Chiquet <julien.chiquet at inrae.fr>
BugReports: https://github.com/jchiquet/aricode/issues
License: GPL (≥ 3)
URL: https://github.com/jchiquet/aricode (dev version)
NeedsCompilation: yes
Language: en-US
Materials: NEWS
CRAN checks: aricode results

Downloads:

Reference manual: aricode.pdf
Package source: aricode_1.0.0.tar.gz
Windows binaries: r-devel: aricode_1.0.0.zip, r-release: aricode_1.0.0.zip, r-oldrel: aricode_1.0.0.zip
macOS binaries: r-release: aricode_1.0.0.tgz, r-oldrel: aricode_1.0.0.tgz
Old sources: aricode archive

Reverse dependencies:

Reverse suggests: missSBM, MoMPCA

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