ROC charts have recently been introduced as a powerful tool for evaluation of learning systems. Although ROC charts are conceptually simple, there are some common misconceptions and pitfalls when used in practice. This work surveys ROC analysis, highlighting the advantages of its use in machine learning and data mining, and tries to clarify several erroneous interpretations related to its use.