Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics (Shanette Luellen's Library) by James Taylor

Author:James Taylor
Language: eng
Format: epub
Publisher: IBM Press
Published: 2012-06-12T16:00:00+00:00

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Some Predictive Analytic Models are not Easy to Represent as Business Rules

There are a number of common predictive analytic models that cannot easily be represented and executed as business rules. These include Linear and Logistic Regression Models, Time Series models, and other statistical-based algorithms that must be represented as a statistical equation as well as those based on neural networks. In addition, segmentation models such as K-Means, Two Step, and Kohonen are generally not easy to represent as business rules because their execution relies on statistical equations or on neural networks. You may be able to use Decision Tree techniques to help identify the rules behind the segments that are generated but this will usually result in an unacceptable level of error being introduced.

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