Evolutionary algorithms in data mining: multi-objective performance modeling for direct marketing

Predictive models in direct marketing seek to identify individuals most likely to respond to promotional solicitations or other intervention programs. While standard modeling approaches embody single objectives, real-world decision problems often seek multiple performance measures. Decision-makers here desire solutions that simultaneously optimize on multiple objectives, or obtain an acceptable tradeoff amongst objectives. Multi-criteria problems often characterize a range of solutions, none of which dominate the others with respect to the multiple objectives - these specify the Pareto-frontier of nondominated solutions, each offering a different level of tradeoff. This paper proposes the use of evolutionary computation based procedures for obtaining a set of nondominated models with respect to multiple stated objectives. The targeting depth-of-file presents a crucial real-world criterion in direct marketing, and models here are tailored for specified file-depths. Decision-makers are ...

• Type: Conference
• Year: 2000
• Where: KDD
• Authors: Siddhartha Bhattacharyya
• Keywords: Data Mining, Embody Single Objectives, KDD 2000, Multiple Objectives, Multiple Stated Objectives