| cartesian_2D | Cartesian Product of Two Vectors |
| ciAUC | Confidence Interval of AUC |
| ciAUC.rocit | Confidence Interval of AUC |
| ciROC | Confidence Interval of ROC curve |
| ciROC.rocit | Confidence Interval of ROC curve |
| ciROCbin | Confidence Interval of Binormal ROC Curve |
| ciROCemp | Confidence Interval of Empirical ROC Curve |
| convertclass | Converts Binary Vector into 1 and 0 |
| Diabetes | Diabetes Data |
| gainstable | Gains Table for Binary Classifier |
| gainstable.default | Gains Table for Binary Classifier |
| gainstable.rocit | Gains Table for Binary Classifier |
| getsurvival | Survival Probability |
| ksplot | KS Plot |
| ksplot.rocit | KS Plot |
| Loan | Loan Data |
| measureit | Performance Metrics of Binary Classifier |
| measureit.default | Performance Metrics of Binary Classifier |
| measureit.rocit | Performance Metrics of Binary Classifier |
| MLestimates | ML Estimate of Normal Parameters |
| plot.gainstable | Plot '"gainstable"' Object |
| plot.rocci | Plot ROC Curve with confidence limits |
| plot.rocit | Plot ROC Curve |
| print.gainstable | Print "gainstable" Object |
| print.measureit | Print "measureit" Object |
| print.rocci | Print 'rocci' Object |
| print.rocit | Print 'rocit' Object |
| print.rocitaucci | Print Confidence Interval of AUC |
| rankorderdata | Rank order data |
| rocit | ROC Analysis of Binary Classifier |
| summary.rocit | Summary of rocit object |
| trapezoidarea | Approximate Area with Trapezoid Rule |