Data defines the model by dint of genetic programming, producing the best decile table.


Extracting Nonlinear Dependencies: An Easy, Automatic Method
Bruce Ratner, Ph.D.

Extracting nonlinear dependencies from the everyclient’s database is the key to successful data mining, ergo, successful predictive modeling. A nonlinear dependency is not the everyday linear combination of important predictor variables defining in part the standard statistical regression model. A nonlinear dependency maybe, say, Sine [{(X2 * (X1 – X2)} * (X1 – X2)]. But, how does one find such a nonlinear dependency? There are many articles on the topic, but no practical solution exists. More importantly, if any solution does exist, no commercial software appears to be readily available. Wrong! The purpose of this article is to present the GenIQ Model (software) as an easy, automatic method for extracting nonlinear dependencies, which when used as input into any predictive modeling approach will outdo any statistical linear method.

For more information about this article, call me at 516.791.3544, or e-mail, br@dmstat1.com.
My publisher owns the copyright of the article, about which this abstract addresses. The article will appear in my forthcoming book.
My publisher has granted me permission to discuss orally the article's content, but by no means provide an outline, a draft or proof-ready of the article.

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