measures (version 0.2)

GMEAN: G-mean

Description

Geometric mean of recall and specificity.

Usage

GMEAN(truth, response, negative, positive)

Arguments

truth

vector of true values

response

vector of predicted values

negative

negative class

positive

positive class

References

He, H. & Garcia, E. A. (2009) *Learning from Imbalanced Data.* IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 9. pp. 1263-1284.

Examples

# NOT RUN {
n = 20
set.seed(125)
truth = as.factor(sample(c(1,0), n, replace = TRUE))
probabilities = runif(n)
response = as.factor(as.numeric(probabilities > 0.5))
positive = 1
negative = 0
GMEAN(truth, response, negative, positive)
# }