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) .


News

NEWS/Changelog

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

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("aricode")

0.1.2 by Julien Chiquet, 3 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