A probabilistic estimation framework for predictive modeling analytics

被引：4
|
作者：
Apte, CV [1 ]
Natarajan, R [1 ]
Pednault, EPD [1 ]
Tipu, FA [1 ]
机构：
[1] IBM Corp, Div Res, Thomas J Watson Res Ctr, Yorktown Hts, NY 10598 USA
来源：
IBM SYSTEMS JOURNAL | 2002年 / 41卷 / 03期
关键词：
D O I：
10.1147/sj.413.0438
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
IBM ProbE (for probabilistic estimation) is an extensible, embeddable, and scalable modeling engine, particularly well-suited for implementing segmentation-based modeling techniques, wherein data records are partitioned into segments and separate predictive models are developed for each segment. We describe the ProbE framework and discuss two key business solutions that have been built using ProbE: the IBM Underwriting Profitability Analysis for insurance risk management, and the IBM Advanced Targeted Marketing for Single Events for direct mail database marketing.
引用
收藏
页码：438 / 448
页数：11
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