This function calculates the Gini index of a classification rule outputting probabilities. It is a classical metric in the context of Credit Scoring.
It is equal to 2 times the AUC (Area Under ROC Curve) minus 1, computed from the ranks of the predictions so that the result does not depend on the order of the observations when predictions are tied.
Usage
normalizedGini(actual, predicted)
Arguments
- actual
The numeric binary vector of the actual labels observed.
- predicted
The vector of the probabilities predicted by the classification rule.
Value
The Gini index of the predicted probabilities as a single num (NA if actual has a single class).
Examples
normalizedGini(c(1, 1, 1, 0, 0), c(0.7, 0.9, 0.5, 0.6, 0.3))
#> [1] 0.6666667