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Direct Marketing Performance Modeling Using Genetic Algorithms.
- Source :
-
INFORMS Journal on Computing . Summer99, Vol. 11 Issue 3, p248. 10p. 1 Graph. - Publication Year :
- 1999
-
Abstract
- 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 be 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DATABASE marketing
*GENETIC algorithms
*DIRECT marketing
Subjects
Details
- Language :
- English
- ISSN :
- 10919856
- Volume :
- 11
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- INFORMS Journal on Computing
- Publication Type :
- Academic Journal
- Accession number :
- 4338362
- Full Text :
- https://doi.org/10.1287/ijoc.11.3.248