A structured view on sources of uncertainty in supervised learning

Abstract

In supervised learning different sources of uncertainty influence the resulting functional behavior of the learning system which increases the risk of misbehavior. But still a learning system is often the only way to handle complex systems and large data sets. Hence it is important to consider the sources of uncertainty and to tackle them as far as possible. In this paper we categorize the sources of uncertainty and give a brief overview of uncertainty handling in supervised learning. © 2012 Springer-Verlag.