MAD Loss in Pattern Recognition and RBF Learning

Authors:
Ewaryst Rafajłowicz;Ewa Skubalska-Rafajłowicz
Affiliations:
Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wrocław, Poland 50 370;Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wrocław, Poland 50 370
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

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Abstract

We consider a multi-class pattern recognition problem with linearly ordered labels and a loss function, which measures absolute deviations of decisions from true classes. In the bayesian setting the optimal decision rule is shown to be the median of a posteriori class probabilities. Then, we propose three approaches to constructing an empirical decision rule, based on a learning sequence. Our starting point is the Parzen-Rosenblatt kernel density estimator. The second and the third approach are based on radial bases functions (RBF) nets estimators of class densities.