ARI: Adjusted Rand Index
In jchiquet/aricode: Efficient Computations of Standard Clustering Comparison Measures
ARI R Documentation
Adjusted Rand Index
Description
A function to compute the adjusted rand index between two classifications
Usage
ARI(c1, c2)
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.
Value
a scalar with the adjusted rand index.
See Also
RI, NID, NVI, NMI, clustComp
Examples
data(iris)
cl <- cutree(hclust(dist(iris[,-5])), 4)
ARI(cl,iris$Species)
jchiquet/aricode documentation built on Feb. 27, 2024, 4:33 p.m.
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| ARI | R Documentation |
Adjusted Rand Index
Description
A function to compute the adjusted rand index between two classifications
Usage
ARI(c1, c2)
Arguments
c1 |
a vector containing the labels of the first classification. Must be a vector of characters, integers, numerics, or a factor, but not a list. |
c2 |
a vector containing the labels of the second classification. |
Value
a scalar with the adjusted rand index.
See Also
RI, NID, NVI, NMI, clustComp
Examples
data(iris)
cl <- cutree(hclust(dist(iris[,-5])), 4)
ARI(cl,iris$Species)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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