The Weighted Bertin Classification Index

The weighted Bertin Classification Criterion using weights according to the Hamming distance is normalized by means of the independence case.

WBCI(x)

Arguments

x	A data matrix.

Value

The criterion value.

See also

kendalls

Examples

M <-arsim(1000, c(12,12), 3)
BCI(M)
#> [1] 0.8537395
WBCI(M)
#> [1] 1.003966


M2 <- optile(M, iter = 100)
BCI(M2)
#> [1] 0.1548857
WBCI(M2)
#> [1] 0.1701929

M3 <- optile(M, fun = "WBCC", iter = 100)
BCI(M3)
#> [1] 0.1620664
WBCI(M3)
#> [1] 0.1551666