International Trade Customers Mining Based on Neuro-Fuzzy Decision Tree
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 FDTs classification accuracy and extracts more accuracy human interpretable classification rules. The fuzzy rules enable a decision-maker to adjust the sale 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 international trade and it will have a good application prospect in this field.
Fuzzy Decision Tree Customers Mining International Trade Neuro-Fuzzy Decision Tree
Jianna Zhao Zhipeng Chang
School of business and Administration, North China Electric Power University Baoding, Hebei 071003, China
国际会议
杭州
英文
1023-1027
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）