A Minimax Solution for Sequential Classification Problems
The purpose of this paper is to derive optimal rules for sequential classification problems. In a sequential classification test, for instance, in an educational context, the decision is to classify a student as a master, a partial master, a nonmaster, or continue testing and administering another random item. The framework of minimax sequential decision theory is used by minimizing the maximum expected losses associated with all possible decision rules at each stage of testing. The main advantage of this approach is that costs of testing can be explicitly taken into account.
KeywordsClassification Decision Optimal Rule Posterior Predictive Distribution Sequential Classification Loss Structure
Unable to display preview. Download preview PDF.
- COOMBS, C.H., DAWES, R.M., and TVERSKY, A. (1970):Mathematical Psychology: An Elementary Introduction. Englewood Cliffs, New Yersey.Google Scholar
- FERGUSON, T.S. (1967): Mathematical Statistics: A Decision Theoretic Approach. Academic Press, New York.Google Scholar
- VOS, H.J. (1998): Compensatory Rules for Optimal Classification With Mastery Scores. In: A. Rizzi, M. Vichy, and H.-H. Bock (Eds.): Advances in Data Science and Classification. Springer, Heidelberg, 211–218.Google Scholar