cc_test_ari: A test for testing the null hypothesis of random agreement...

In CrossClustering: A Partial Clustering Algorithm

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

Description

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

Usage

cc_test_ari(ground_truth, partition)

Arguments

ground_truth	(int) A vector of the actual membership of elements in clusters
partition	The partition coming from a clustering algorithm

Value

A list with six elements:

Rand	the Rand Index
ExpectedRand	expected value of Rand Index
AdjustedRand	Adjusted Rand Index
var_ari	variance of Rand Index
nari	nari
p-value	the p-value of the test

Author(s)

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

References

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.

Examples

library(CrossClustering)

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

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

cc_test_ari(ground_truth, clusters)

CrossClustering documentation built on May 29, 2024, 9:22 a.m.