B1000                   Balanced data with 1000 positives and 1000
                        negatives.
B500                    Balanced data with 500 positives and 500
                        negatives.
IB1000                  Imbalanced data with 1000 positives and 10000
                        negatives.
IB500                   Imbalanced data with 500 positives and 5000
                        negatives.
M2N50F5                 5-fold cross validation sample.
P10N10                  A small example dataset with several tied
                        scores.
as.data.frame           Convert a curves and points object to a data
                        frame
auc                     Retrieve a data frame of AUC scores
auc_ci                  Calculate CIs of ROC and precision-recall AUCs
autoplot                Plot performance evaluation measures with
                        ggplot2
create_sim_samples      Create random samples for simulations
evalmod                 Evaluate models and calculate performance
                        evaluation measures
format_nfold            Create n-fold cross validation dataset from
                        data frame
fortify                 Convert a curves and points object to a data
                        frame for ggplot2
join_labels             Join observed labels of multiple test datasets
                        into a list
join_scores             Join scores of multiple models into a list
mmdata                  Reformat input data for performance evaluation
                        calculation
part                    Calculate partial AUCs
pauc                    Retrieve a data frame of pAUC scores
plot                    Plot performance evaluation measures
precrec                 precrec: A package for computing accurate ROC
                        and Precision-Recall curves
