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), normalized variation information (NVI) and entropy, as described in Vinh et al (2009) . Include AMI (Adjusted Mutual Information) since version 0.1.2, a modified version of ARI (MARI), as described in Sundqvist et al. and simple Chi-square distance since version 1.0.0.


Reference manual

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install.packages("aricode")

1.1.0 by Julien Chiquet, 5 months ago


https://github.com/jchiquet/aricode


Report a bug at https://github.com/jchiquet/aricode/issues


Browse source code at https://github.com/cran/aricode


Authors: Julien Chiquet [aut, cre] (ORCID: , Guillem Rigaill [aut] , Martina Sundqvist [aut] , Valentin Dervieux [ctb] , Florent Bersani [ctb]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports Matrix, Rcpp, lifecycle

Suggests testthat, spelling, mclust, ggplot2, pkgdown

Linking to Rcpp


Imported by GREMLINS, JANE, MCseqReplic, SISIR, clustAnalytics, l1spectral, manydist, scStability.

Suggested by FCPS, FisherEM, TextAnalysisR, missSBM, normalblockr, sbm.


See at CRAN