visualises how class 1 and class 0 classification error (CLE) differs in each trained calibration model. Comparing class-specific CLE helps to choose a calibration model for applications were classification error is cost-sensitive for one class. See get_CLE_class for details on the implementation.
get_CLE_comparison(list_models)
Arguments
list_models: list object that contains all error values for all trained calibration models. For the specific format, see the calling function visualize_calibratR.