trains and evaluates the GUESS calibration model using folds-Cross-Validation (CV).
The predicted values are partitioned into n subsets. A GUESS model is constructed on (n-1) subsets; the remaining set is used
for testing the model. All test set predictions are merged and used to compute error metrics for the model.
GUESS_CV(actual, predicted, n_folds = 10, method_of_prediction = 2, seed,
input)vector of observed class labels (0/1)
vector of uncalibrated predictions
number of folds for the cross-validation, Default: 10
PARAM_DESCRIPTION, Default: 2
random seed to alternate the split of data set partitions
specify if the input was scaled or transformed, scaled=1, transformed=2
list object containing the following components:
list object that summarizes discrimination and calibration errors obtained during the CV
"GUESS"
which prediction method was used during CV
vector of calibrated predictions that was used during the CV
respective vector of true values (0 or 1) that was used during the CV