Design of a classifier consists of two stages: feature extraction and classifier learning. For a better performance, the nature, characteristics, or underlying structure of data should be taken into account in either of the stages when we design a classifier. In this thesis, we present kernel...

In this paper, we develop a decision-theoretic frameworkfor evaluating data mining systems, which employ classification methods, in terms of their utility in decision-making. The decision-theoretic model provides an economic perspective on the value of â extracted knowledge,â in terms of its...