Abstract
The paper deals with the multistage recognition task. In this problem of recognition the Bayesian statistic is applied. The decision rules minimize the mean risk, that is the mean value of the zero-one loss function. The information on objects features is fuzzy or non-fuzzy. The probability of misclassification for local optimal strategy and the difference between probability of misclassification for the both information’s are presented. Simple example of this difference conclude the work.
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Burduk, R. (2007). Classification Accuracy in Local Optimal Strategy of Multistage Recognition with Fuzzy Data. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_46
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DOI: https://doi.org/10.1007/978-3-540-75175-5_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75174-8
Online ISBN: 978-3-540-75175-5
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