calculates the class-specific classification error CLE in the test set. The method computes the deviation of the calibrated predictions of class 1 instances from their true value 1. For class 0 instances, get_CLE_class computes the deviation from 0. Class 1 CLE is 0 when all class 1 instances have a calibrated prediction of 1 regardless of potential miscalibration of class 0 instances. CLE calculation is helpful when miscalibration and -classification is more cost-sensitive for one class than for the other.
get_CLE_class(actual, predicted, bins =10)
Arguments
actual: vector of observed class labels (0/1)
predicted: vector of uncalibrated predictions
bins: number of bins for the equal-width binning model, default=10
Returns
object of class list containing the following components: - class_1: CLE of class 1 instances