Construction of Bayesian Classifiers with GA for Response Modeling in Direct Marketing

摘要：

In this paper, a Bayesian classifier for modeling consumer response to direct marketing is constructed based on a novel genetic algorithm (GA). To evaluate the performance of this model, we test it with a large amount of validation data of direct marketing and compare the results with other benchmark methods, including Recency-Frequency-Monetary (RFM) analysis, Chi-Square automatic interaction detector (CHAID), Logistic regression (LR) and so on. The results demonstrate the superiority of this model over the others in terms of accuracy of prediction and interpretable of results. Recently, it has been adopted by a credit card company to effectively handle business problems.

作者: Hongmei Shao Gaofeng Zheng

作者单位: College of Math. and Comput. Science China University of Petroleum Dongying, 257061, China JANA Solutions, Inc. Shiba 1-15-13, Minato-ku Tokyo, 105-0014, Japan

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Computer Science and Information Technology(第二届计算机科学与信息技术国际会议 ICCSIT2009)

会议地点: 北京

会议语种:英文

页码: 2028-2032

在线出版日期: 2009-08-08（万方平台首次上网日期，不代表论文的发表时间）