compare.adjrand {T4cluster} | R Documentation |
(+) Adjusted Rand Index
Description
Compute Adjusted Rand index between two clusterings. Please note that the value can yield negative value.
Usage
compare.adjrand(x, y)
Arguments
x |
1st cluster label vector of length- |
y |
2nd cluster label vector of length- |
Value
Adjusted Rand Index value.
See Also
Examples
# -------------------------------------------------------------
# true label vs. clustering with 'iris' dataset
# -------------------------------------------------------------
## PREPARE
data(iris)
X = as.matrix(iris[,1:4])
lab = as.integer(as.factor(iris[,5]))
## CLUSTERING WITH DIFFERENT K VALUES
vec_k = 2:7
vec_cl = list()
for (i in 1:length(vec_k)){
vec_cl[[i]] = T4cluster::kmeans(X, k=round(vec_k[i]))$cluster
}
## COMPUTE COMPARISON INDICES
vec_comp = rep(0, length(vec_k))
for (i in 1:length(vec_k)){
vec_comp[i] = compare.adjrand(vec_cl[[i]], lab)
}
## VISUALIZE
opar <- par(no.readonly=TRUE)
plot(vec_k, vec_comp, type="b", lty=2, xlab="number of clusters",
ylab="comparison index", main="Adjusted Rand Index with true k=3")
abline(v=3, lwd=2, col="red")
par(opar)
[Package T4cluster version 0.1.2 Index]