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Data defines the model by dint of genetic programming, producing the best decile table.
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Extra-GenIQ Applications Bruce Ratner, Ph.D. |
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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:
- Overfitting: Old Problem, New Solution
- Data Cleaning is Not Completed Until the “Noise” is Eliminated
- GenIQ-enhanced Regression Model
- GenIQ-enhanced/Data-reused Regression
- A Method for Moderating Outliers, Instead of Discarding Them
- How to Make the Best Credit Score Even Better
- GenIQ: Nonlinear Curve Fitter
GenIQ: OLS Curve Fitter
- Real World Data are Dirty: Data Cleaning and the "Noise" Problem
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| 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. |
| Sign-up for a free GenIQ webcast: Click here. |
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