Game theoretical pattern recognition: application to imperfect noncooperative learning and to multiclass classification |
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Authors: | Pau L F |
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Affiliation: | Battelle Memorial Institute, 7 Route de Drize, CH-1227 Carouge, Switzerland.; |
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Abstract: | This paper studies in theory, and gives a solution to, the following concerns which may eventually be simultaneous: 1) obtain alternative classification decisions, ranked by some decreasing order of class membership probabilities; 2) imperfect teacher at the learning stage, or effects of labeling errors due to unsupervised learning by clustering; 3) noncooperative teacher, manipulating the a priori class probabilities; 4) unknown a priori class probabilities. These requirements are taken into account by considering a game between the recognition system and the teacher, in a game theoretical framework. Both players will ultimately select ``mixed strategies,' which are probability distributions over the set of N alternative pattern classes, determined for each feature vector to be classified. This solution concept is interpreted in terms of the requirements 1)-4); numerical algorithms, as well as numerical examples are given with their solutions. |
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