R: Examples for 'mclust::classError'

### ** Examples

(a <- rep(1:3, 3))

[1] 1 2 3 1 2 3 1 2 3

(b <- rep(c("A", "B", "C"), 3))

[1] "A" "B" "C" "A" "B" "C" "A" "B" "C"

classError(a, b)

$misclassified
integer(0)

$errorRate
[1] 0

(a <- sample(1:3, 9, replace = TRUE))

[1] 1 1 2 1 3 2 1 2 2

(b <- sample(c("A", "B", "C"), 9, replace = TRUE))

[1] "A" "A" "A" "A" "A" "A" "A" "A" "B"

classError(a, b)

$misclassified
[1] 3 5 6 8

$errorRate
[1] 0.4444444

class <- factor(c(5,5,5,2,5,3,1,2,1,1), levels = 1:5)
probs <- matrix(c(0.15, 0.01, 0.08, 0.23, 0.01, 0.23, 0.59, 0.02, 0.38, 0.45,
                  0.36, 0.05, 0.30, 0.46, 0.15, 0.13, 0.06, 0.19, 0.27, 0.17,
                  0.40, 0.34, 0.18, 0.04, 0.47, 0.34, 0.32, 0.01, 0.03, 0.11,
                  0.04, 0.04, 0.09, 0.05, 0.28, 0.27, 0.02, 0.03, 0.12, 0.25,
                  0.05, 0.56, 0.35, 0.22, 0.09, 0.03, 0.01, 0.75, 0.20, 0.02),
                nrow = 10, ncol = 5)
cbind(class, probs, map = map(probs))

      class                          map
 [1,]     5 0.15 0.36 0.40 0.04 0.05   3
 [2,]     5 0.01 0.05 0.34 0.04 0.56   5
 [3,]     5 0.08 0.30 0.18 0.09 0.35   5
 [4,]     2 0.23 0.46 0.04 0.05 0.22   2
 [5,]     5 0.01 0.15 0.47 0.28 0.09   3
 [6,]     3 0.23 0.13 0.34 0.27 0.03   3
 [7,]     1 0.59 0.06 0.32 0.02 0.01   1
 [8,]     2 0.02 0.19 0.01 0.03 0.75   5
 [9,]     1 0.38 0.27 0.03 0.12 0.20   1
[10,]     1 0.45 0.17 0.11 0.25 0.02   1

classError(map(probs), class)

$misclassified
[1] 2 3 8

$errorRate
[1] 0.3

Examples for 'mclust::classError'

Classification error