Abstract
In this paper, a model to deal with Bayesian hierarchical classifier, in which consequences of decision are fuzzy-valued, is introduced. The model is based on the notion of fuzzy random variable and also on a subjective ranking method for fuzzy number defined by Campos and González. The Bayesian hierarchical classifier is based on a decision-tree scheme for given tree skeleton and features to be used in each inertial nodes. The influence of selection of fuzzy-valued loss function on classification result is given. Finally, an example illustrating this case of Bayesian analysis is considered.
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© 2005 Springer-Verlag Berlin Heidelberg
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Burduk, R. (2005). Selection of Fuzzy-Valued Loss Function in Two Stage Binary Classifier. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_12
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DOI: https://doi.org/10.1007/3-540-32390-2_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
Online ISBN: 978-3-540-32390-7
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