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A probabilistic estimation framework for predictive modeling analytics

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4 Author(s)
C. V. Apte ; IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598, USA ; R. Natarajan ; E. P. D. Pednault ; F. A. Tipu

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.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Systems Journal  (Volume:41 ,  Issue: 3 )