R: Performance Assessment of Binary Classifier with Visualization

# Performance Assessment of Binary Classifier with Visualization

## Documentation for package ‘ROCit’ version 2.1.2

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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