Comments on real-valued negative selection vs. real-valued positive selection and one-class SVM

Real-valued negative selection (RVNS) is an immune-inspired technique for anomaly detection problems. It has been claimed that this technique is a competitive approach, comparable to statistical anomaly detection approaches such as one-class Support Vector Machine. Moreover, it has been claimed that the complementary approach to RVNS, termed real-valued positive selection, is not a realistic solution. We investigate these claims and show that these claims can not be sufficiently supported.