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Probability of Misclassification in Bayesian Hierarchical Classifier

Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 31)

Abstract

The paper deals with the probability of misclassification in a multistage classifier. This classification problem is based on a decision-tree scheme. For given tree skeleton and features to be used, the Bayes decision rules at each non-terminal node are presented. Additionally the information on objects features is fuzzy or nonfuzzy. The upper bound of the difference between probability of misclassification for the both information’s is presented. In the paper we use the maximum likelihood estimator for fuzzy data.

Keywords

Fuzzy Number Fuzzy Triangular Number Interior Node Fuzzy Information Fuzzy Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  1. 1.Wrocław University of TechnologyWrocławPoland

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