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>.

Version: 0.1.2
Imports: Matrix, Rcpp
LinkingTo: Rcpp
Suggests: testthat
Published: 2019-06-29
Author: Julien Chiquet ORCID iD [aut, cre], Guillem Rigaill [aut], Valentin Dervieux [ctb]
Maintainer: Julien Chiquet <julien.chiquet at inra.fr>
BugReports: https://github.com/jchiquet/aricode/issues
License: GPL (≥ 3)
URL: https://github.com/jchiquet/aricode (dev version)
NeedsCompilation: yes
Materials: NEWS
CRAN checks: aricode results

Downloads:

Reference manual: aricode.pdf
Package source: aricode_0.1.2.tar.gz
Windows binaries: r-devel: aricode_0.1.2.zip, r-release: aricode_0.1.2.zip, r-oldrel: aricode_0.1.2.zip
OS X binaries: r-release: aricode_0.1.2.tgz, r-oldrel: aricode_0.1.2.tgz
Old sources: aricode archive

Reverse dependencies:

Reverse suggests: missSBM

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