Selection of Fuzzy-Valued Loss Function in Two Stage Binary Classifier
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.
KeywordsLoss Function Fuzzy Number Recognition Algorithm Decision Region Fuzzy Random Variable
Unable to display preview. Download preview PDF.
- 7.Gil M, López-Díaz M (1996) A Model for Bayesian Decision Problems Involving Fuzzy-Valued Consequences. Proc. 6th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge Based Systems, GranadaGoogle Scholar
- 12.Viertl R (1996) Statistical Methods for Non-Precise Data. CRC Press, Boca RatonGoogle Scholar