CrossClustering (version 4.0.3)

cc_test_ari: 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

varARI

variance of Rand Index

NARI

NARI

p-value

the p-value of the test

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

# NOT RUN {
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)

# }