Abstract

In the paper we consider the two-stage binary classifier based on Bayes rule. Assuming that both the tree structure and the feature used at each non-terminal node have been specified, we present the expected total cost. This cost is considered for two types of loss function. First is the zero-one loss function and second is the node-dependent fuzzy loss function. The work focuses on the difference between the expected total costs for these two cases of loss function in the two-stage binary classifier. The obtained results are presented on the numerical example.

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