A Generalized Model for Predictive Data Mining

被引：0
作者：
James V. Hansen
James B. McDonald
机构：
[1] Brigham Young University,Marriott School of Management
[2] Brigham Young University,Department of Economics
来源：
Information Systems Frontiers | 2002年 / 4卷
关键词：
data mining; prediction; choice estimator; misclassification costs;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper describes a flexible model for predictive data mining, EGB2, which optimizes over a parameter space to fit data to a family of models based on maximum-likelihood criteria. It is also shown how EGB2 can integrate asymmetric costs of Type I and Type II errors, thereby minimizing expected misclassification costs.
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收藏
页码：179 / 186
页数：7
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