plotROC: A Tool for Plotting ROC Curves

ROC Curves for Steganalysts

There are different approaches in the literature for the assessment of steganographic algorithms and steganalytic attacks. In the early papers it was considered sufficient to show the existence of an effect for one or a few examples only. The more the area of steganography evolved, the more diverse became the goals and the harder to measure the improvements. Many branches of science are facing ...

Confidence Bands for ROC Curves

We address the problem of comparing the performance of classifiers. In this paper we study techniques for generating and evaluating confidence bands on ROC curves. Historically this has been done using one-dimensional confidence intervals by freezing one variable—the false-positive rate, or threshold on the classification scoring function. We adapt two prior methods and introduce a new radial s...

Resampling ROC curves

Receiver operating characteristic (ROC) curves are very popular for evaluating a diagnostic test or score performances in various decision making applications: medicine, marketing, credit scoring etc. The ROC curve provides a concise graphical representation of the trade off between sensitivity and specificity. We will focus here on supervised classification into two groups. Error rate estimati...

ROC curves are a suitable and flexible tool for the analysis of gene expression profiles.

ROC Curves for Multivariate Biometric Matching Models

The biometric matching problem is a two class (“within” or “between”) classification problem where two types of errors (FRR and FAR) occur. While the receiver operating characteristic or ROC curve, which is a plot of FRR and FAR, can be easily obtained in the simple matching model, it is non-trivial to obtain in the multivariate matching model. Here the problem of obtaining ROC curves for sever...