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

A New Method of Decile Analysis Optimization for Database Models
Bruce Ratner, Ph.D.

Using a variety of techniques, data analysts in database marketing aim to build models that maximize expected response and profit from solicitations. Standard techniques include the statistical methods of classical discriminant analysis, as well as logistic and ordinary regression. A recent addition in the data analysis arsenal is the GenIQ Model© - a hybrid machine learning- statistics method - which is presented in full detail below.

First, a background on the concept of optimization will be helpful since optimization techniques provide the estimation of all models. Genetic modeling is the "engine" for the GenIQ Model, and is discussed next as a machine learning optimization approach. Since the objective of database models is decile analysis optimization, i.e., to maximize expected response or profit from solicitations, I will demonstrate how the GenIQ Model serves to meet that objective. Actual case studies are presented to further explicate the potential of the GenIQ Model.
For more information about this article, call Bruce Ratner at 516.791.3544 or 1 800 DM STAT-1; or e-mail at
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