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) .



0.1-1 (2018-04-30) + first submission to CRAN

Reference manual

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0.1.2 by Julien Chiquet, 8 months ago

https://github.com/jchiquet/aricode (dev version)

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

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

Authors: Julien Chiquet [aut, cre] , Guillem Rigaill [aut] , Valentin Dervieux [ctb]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports Matrix, Rcpp

Suggests testthat

Linking to Rcpp

Suggested by missSBM.

See at CRAN