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), normalized variation information (NVI) and entropy, as described in Vinh et al (2009) <doi:10.1145/1553374.1553511>.

Getting started

Package details

AuthorJulien Chiquet [aut, cre] (<https://orcid.org/0000-0002-3629-3429>), Guillem Rigaill [aut], Valentin Dervieux [ctb]
MaintainerJulien Chiquet <[email protected]>
LicenseGPL (>= 3)
Version0.1.1
URL https://github.com/jchiquet/aricode (dev version)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("aricode")

Try the aricode package in your browser

Any scripts or data that you put into this service are public.

aricode documentation built on May 3, 2018, 1:05 a.m.