R: Adjusted Rand Index

adjustedRandIndex {mclust} | R Documentation

## Adjusted Rand Index

### Description

Computes the adjusted Rand index comparing two classifications.

### Usage

    adjustedRandIndex(x, y)

### Arguments

`x` | A numeric or character vector of class labels.
`y` | A numeric or character vector of class labels. The length of `y` should be the same as that of `x`.

### Value

The adjusted Rand index comparing the two partitions (a scalar). This index has zero expected value in the case of random partition, and it is bounded above by 1 in the case of perfect agreement between two partitions.

### References

L. Hubert and P. Arabie (1985) Comparing Partitions, Journal of the Classification, 2, pp. 193-218.

### See Also

`classError`, `mapClass`, `table`

### Examples

    a <- rep(1:3, 3)
    a
    b <- rep(c("A", "B", "C"), 3)
    b
    adjustedRandIndex(a, b)

    a <- sample(1:3, 9, replace = TRUE)
    a
    b <- sample(c("A", "B", "C"), 9, replace = TRUE)
    b
    adjustedRandIndex(a, b)

    a <- rep(1:3, 4)
    a
    b <- rep(c("A", "B", "C", "D"), 3)
    b
    adjustedRandIndex(a, b)

    irisHCvvv <- hc(modelName = "VVV", data = iris[,-5])
    cl3 <- hclass(irisHCvvv, 3)
    adjustedRandIndex(cl3,iris[,5])

    irisBIC <- mclustBIC(iris[,-5])
    adjustedRandIndex(summary(irisBIC,iris[,-5])$classification,iris[,5])
    adjustedRandIndex(summary(irisBIC,iris[,-5],G=3)$classification,iris[,5])

[Package mclust version 5.4.8 Index]