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) . 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.



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

Reference manual

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1.0.0 by Julien Chiquet, 2 years 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] , Martina Sundqvist [aut] , Valentin Dervieux [ctb]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports Matrix, Rcpp

Suggests testthat, spelling

Linking to Rcpp

Imported by GREMLINS, doMIsaul, l1spectral.

Suggested by FisherEM, MoMPCA, missSBM, sbm.

See at CRAN