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.
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Burduk, R. (2005). Probability of Misclassification in Bayesian Hierarchical Classifier. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32392-9_35
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DOI: https://doi.org/10.1007/3-540-32392-9_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25056-2
Online ISBN: 978-3-540-32392-1
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