easyROC: a web-tool for ROC curve analysis. A receiver operating characteristics (ROC) curve is a graphical approach which assess the performance of a binary classifier system. The ROC curve analysis is widely used in medicine, radiology, biometrics and various application of machine learning. Here we developed an easy way to carry out ROC analysis. This application creates ROC curves, calculates area under the curve (AUC) values and confidence intervals for the AUC values, and performs multiple comparisons for ROC curves in a user-friendly, up-to-date and comprehensive way. Moreover, easyROC computes and compares partial AUCs. It can also perform sample size calculation.
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References in zbMATH (referenced in 2 articles , 1 standard article )
Showing results 1 to 2 of 2.
- Waldemar W. Koczkodaj, Alicja Wolny-Dominiak: RatingScaleReduction package: stepwise rating scale item reduction without predictability loss (2017) arXiv
- Dincer Goksuluk, Selcuk Korkmaz, Gokmen Zararsiz, A. Ergun Karaagaoglu: easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment (2016) not zbMATH