GUESS_CV: GUESS_CV
In CalibratR: Mapping ML Scores to Calibrated Predictions

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.

1 2	GUESS_CV(actual, predicted, n_folds = 10, method_of_prediction = 2, seed, input)

`actual`	vector of observed class labels (0/1)
`predicted`	vector of uncalibrated predictions
`n_folds`	number of folds for the cross-validation, Default: 10
`method_of_prediction`	PARAM_DESCRIPTION, Default: 2
`seed`	random seed to alternate the split of data set partitions
`input`	specify if the input was scaled or transformed, scaled=1, transformed=2

list object containing the following components:

`error`	list object that summarizes discrimination and calibration errors obtained during the CV
`type`	"GUESS"
`pred_idx`	which prediction method was used during CV
`probs_CV`	vector of calibrated predictions that was used during the CV
`actual_CV`	respective vector of true values (0 or 1) that was used during the CV