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)
- Version1.0.3
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Languageen-US
- Last release10/20/2023
Documentation
Team
Julien Chiquet
Guillem Rigaill
Show author detailsRolesAuthorMartina Sundqvist
Show author detailsRolesAuthorValentin Dervieux
Show author detailsRolesContributorFlorent Bersani
Show author detailsRolesContributor
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