cc_test_ari: A test for testing the null hypothesis of random agreement...
In CrossClustering: A Partial Clustering Algorithm

Description Usage Arguments Value Author(s) References Examples

A test for testing the null hypothesis of random agreement (i.e., adjusted Rand Index equal to 0) between two partitions.

1	cc_test_ari(ground_truth, partition)

`ground_truth`	[int] A vector of the actual membership of elements in clusters
`partition`	The partition coming from a clustering algorithm

A list with six elements:

`Rand`	the Rand Index
`ExpectedRand`	expected value of Rand Index
`AdjustedRand`	Adjusted Rand Index
`varARI`	variance of Rand Index
`NARI`	NARI
`p-value`	the p-value of the test

Paola Tellaroli, <paola [dot] tellaroli [at] unipd [dot] it>; Philippe Courcoux, <philippe [dot] courcoux [at] oniris-nantes [dot] fr>

E_M. Qannari, P. Courcoux and Faye P. (2014) Significance test of the adjusted Rand index. Application to the free sorting task, Food Quality and Preference, (32)93-97

L. Hubert and P. Arabie (1985) Comparing partitions, Journal of Classification, 2, 193-218.

library(CrossClustering)

clusters <- iris[-5] %>%
  dist %>%
  hclust(method = 'ward.D') %>%
  cutree(k = 3)

ground_truth <- iris[[5]] %>% as.numeric()

CrossClustering:::cc_test_ari(ground_truth, clusters)