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A Subclass Model for Nonlinear Pattern Classification
Pattern Recognition Letters
  • Qiuming Zhu, University of Nebraska at Omaha
  • Yao Cai, University of Nebraska at Omaha
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This paper describes a pattern classification model called “classification on subclasses”. The model and its computation scheme are based on the theoretic foundation of minimizing the cross-entropy of the distribution functions that bear considerable complexity and non-linearity. In this model, pattern classes are configured and described by a number of subclasses each associated with a distribution formulated according to the regularization principle. This modeling technique provides a simplified solution to a group of non-linear pattern classification problems. Simulation shows a high classification rate on pattern samples with complex distributions.
Citation Information
Qiuming Zhu and Yao Cai. "A Subclass Model for Nonlinear Pattern Classification" Pattern Recognition Letters Vol. 19 Iss. 1 (1998) p. 19 - 29
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