What is an ROC curve?
An ROC curve demonstrates the tradeoff between true-positive rate and false positive rate in binary classification problems as a function of varying a classification threshold. The method was pioneered in evaluating radar operators where it was given the name: receiver operating characteristic curve. The method gained popularity among statisticians for evaluating diagnosis tests, and was later adopted by the machine learning community for general binary classification evaluation. ROC curves are similar to the precision/recall curves used in information retrieval as well as lift curves used in marketing communities. Our .java files include code for generating Empirical ROC curves (EmpiricalROCMaker.java). An empirical ROC curve is a curve plotted using the empirical distribution of the data as opposed to using a smoothing function. We built this package after trying out several free packages designed for medical diagnosis evaluation. These tools had many useful features including confid
