Calculate the area under the curve (AUC)

Calculate the area under the curve (AUC)

get_auc(roc)

Arguments

roc	a matrix or data frame with columns "FPR" and "TPR" containing pairs of false and true positive rates.#'

Examples

# simulate training and test data
dat <- data.frame(
    cl = as.factor(rbinom(10, 1, 0.5)),
    x1 = rnorm(10),
    x2 = rbinom(10, 1, 0.3)
)

model <- jdify(cl ~ x1 + x2, data = dat)      # joint density fit
probs <- predict(model, dat, what = "probs")  # conditional probabilities

# calculate performance measures
assess_clsfyr(probs[, 1], dat[, 1] == 0, measure = c("ACC", "F1"))
#>    threshold measure     value
#> 1        0.0     ACC 0.8000000
#> 2        0.1     ACC 0.8000000
#> 3        0.2     ACC 0.8000000
#> 4        0.3     ACC 0.8000000
#> 5        0.4     ACC 0.8000000
#> 6        0.5     ACC 0.8000000
#> 7        0.6     ACC 0.8000000
#> 8        0.7     ACC 0.4000000
#> 9        0.8     ACC 0.3000000
#> 10       0.9     ACC 0.3000000
#> 11       1.0     ACC 0.3000000
#> 12       0.0      F1 0.8888889
#> 13       0.1      F1 0.8888889
#> 14       0.2      F1 0.8888889
#> 15       0.3      F1 0.8888889
#> 16       0.4      F1 0.8888889
#> 17       0.5      F1 0.8888889
#> 18       0.6      F1 0.8888889
#> 19       0.7      F1 0.4000000
#> 20       0.8      F1 0.2222222
#> 21       0.9      F1 0.2222222
#> 22       1.0      F1 0.2222222

# calculate area under the curve
FPR <- assess_clsfyr(probs[, 1], dat[, 1] == 0, measure = c("FPR"))$value
TPR <- assess_clsfyr(probs[, 1], dat[, 1] == 0, measure = c("TPR"))$value
get_auc(data.frame(FPR = FPR, TPR = TPR))
#>        [,1]
#> [1,] 0.5625