A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
We have previously introduced the Learn++ algorithm that provides surprisingly promising performance for incremental learning as well as data fusion applications. In this contribut...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...