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- W2145185494 abstract "Fuzzy decision tree (FDT) is a powerful, top-down, hierarchical search methodology to extract human interpretable classification rules. However, it is poor in classification accuracy. In this paper, neural networks-fuzzy decision tree (Neuro-FDT) is constructed using the method of Rajen B. Bhatt and Gopal: a fuzzy decision tree structure with neural like parameter adaptation strategy. The method improves FDT's classification accuracy and extracts more accuracy human interpretable classification rules. The fuzzy rules enable a decision-maker to adjust corresponding strategy according to different customers. The decision-maker may give some special policies to higher-profit customers. The results of the research indicate that the Neuro-fuzzy decision tree technique is very valid in Logistics industry and it will have a good application prospect in this field." @default.
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- W2145185494 date "2007-08-01" @default.
- W2145185494 modified "2023-10-03" @default.
- W2145185494 title "Customers Mining of Logistics Industry Based on Neuro-Fuzzy Decision Tree" @default.
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- W2145185494 doi "https://doi.org/10.1109/ical.2007.4338587" @default.
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