In this article, you will learn what a ROC curve is, how to interpret it, and why it is important for machine learning model validation. A ROC curve stands for receiver operating characteristic curve.

The AUC-ROC metric clearly helps determine and tell us about the capability of a model in distinguishing the classes. The judging criteria being - Higher the AUC, better the model. AUC-ROC curves are ...

The area under the ROC curve (AUC) measures the performance of a machine learning algorithm. ROC curves visualize the statistical accuracy of classifier selection.[1] ...

In this article, we will learn more about the ROC-AUC curve and how we make use of it to compare different machine learning models to select the best performing model. For this experiment, we will ...

Abstract: In recent years, the problem of learning ... importance in machine learning literature. Here, we propose a supervised algorithm that learns a ranking function, called ranking instances by ...