NMI: Normalized mutual information (NMI)

In aricode: Efficient Computations of Standard Clustering Comparison Measures

Normalized mutual information (NMI)

Description

A function to compute the NMI between two classifications

Usage

NMI(c1, c2, variant = c("max", "min", "sqrt", "sum", "joint"))

Arguments

c1	a vector containing the labels of the first classification. Must be a vector of characters, integers, numerics, or a factor, but not a list.
c2	a vector containing the labels of the second classification.
variant	a string in ("max", "min", "sqrt", "sum", "joint"): different variants of NMI. Default use "max".

Value

a scalar with the normalized mutual information .

See Also

RI, NID, NVI, ARI, clustComp

Examples

data(iris)
cl <- cutree(hclust(dist(iris[,-5])), 4)
NMI(cl,iris$Species)

aricode documentation built on Oct. 20, 2023, 5:07 p.m.