Direct marketing performance modeling using genetic algorithms

被引:34
作者
Bhattacharyya, S [1 ]
机构
[1] Univ Illinois, Coll Business Adm, Chicago, IL 60607 USA
关键词
D O I
10.1287/ijoc.11.3.248
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Data analysts in direct marketing seek models to identify the most promising individuals to mail to and thus maximize returns from solicitations. A variety of criterion can he used to assess model performance, including response to or revenue generated from earlier solicitations. Given budgetary limitations, typically a fraction of the total customer database is selected for mailing. This depth-of-file that is to be mailed to provides potentially useful Information that should be considered In model determination. This article presents a genetic algorithm-based approach for obtaining models in explicit consideration of this mailing depth. Issues related to overfitting, common in application of machine learning techniques, are examined, and experiments are based on a real-life data set.
引用
收藏
页码:248 / 257
页数:10
相关论文
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