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


Extra-GenIQ Applications
Bruce Ratner, Ph.D.

The GenIQ Model is a machine learning alternative model to the statistical ordinary least squares and logistic regression models.
GenIQ lets the data define the model – automatically data mines for new variables, performs variable selection, and then specifies the model equation – so as to "optimize the decile table," to fill the upper deciles with as much profit/many responses as possible. Put differently, GenIQ seeks to maximize cum lift, a measure of model predictiveness of identifying the upper performing individuals often displayed in a decile table. GenIQ produces models that outdo statistical models, and is a different model: unsuspected equation, ungainly interpretation, and easy implementation. 


Beyond GenIQs original application as an automatic model building, data mining tool, GenIQ performs extra-GenIQ applications:

  1. Overfitting: Old Problem, New Solution
  2. Data Cleaning is Not Completed Until the “Noise” is Eliminated
  3. GenIQ-enhanced Regression Model
  4. GenIQ-enhanced/Data-reused Regression
  5. A Method for Moderating Outliers, Instead of Discarding Them
  6. How to Make the Best Credit Score Even Better 
  7. GenIQ: Nonlinear Curve Fitter
  8. GenIQ: OLS Curve Fitter
  9. Real World Data are Dirty: Data Cleaning and the "Noise" Problem


                                         

For more information about this article, call Bruce Ratner at 516.791.3544 or 1 800 DM STAT-1; or e-mail at br@dmstat1.com.
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