For direct marketing forecasting models, this study applied machine learning and stochastic optimization using Bayesian networks learned by evolutionary programming. The results of a ten-fold cross-validation experiment suggest that Bayesian networks have distinctive advantages over competing methods in accuracy of forecast, transparency of procedures, interpretability of results, and explanatory insight.
|Publication status||Published - 2005|
|Event||Triennial Meeting of the International Federation of the Operation Research Societies - United States, Hawaii, United States|
Duration: 1 Jul 2005 → 1 Jul 2005
|Conference||Triennial Meeting of the International Federation of the Operation Research Societies|
|Abbreviated title||IFORS Triennial Conference|
|Period||1/07/05 → 1/07/05|
CUI, G., & WONG, M. L. (2005). Bayesian Networks Learned with Evolutionary Programming for Direct Marketing Forecasting. Paper presented at Triennial Meeting of the International Federation of the Operation Research Societies, Hawaii, United States.