# The GenIQ Model Modeling and Data Mining Software

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*Here are a few words on the GenIQ model, from Bruce Ratner.*

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.

Database Marketing (DM) regression models seek to maximize *cum lift*, a measure of model predictiveness of identifying the *upper* performing individuals often displayed in a *decile table*. DM regression models built on today’s *big data* – consisting of a *multitude* of variables, an *army* of observations – using statistical regression models, conceived and testing within the *small-data setting* of the day, 205 years ago, is …

*Here are a few words on the GenIQ model, from Bruce Ratner.*

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.

Database Marketing (DM) regression models seek to maximize *cum lift*, a measure of model predictiveness of identifying the *upper* performing individuals often displayed in a *decile table*. DM regression models built on today’s *big data* – consisting of a *multitude* of variables, an *army* of observations – using statistical regression models, conceived and testing within the *small-data setting* of the day, 205 years ago, is problematic: Fitting big data to a pre-specified *small-framed* model produces a *skewed* model with doubtful interpretability and questionable results. The GenIQ Model is a machine-learning alternative regression model to the statistical models. It is an assumption-free, free-form model that maximizes cum lift, equivalently, the decile table. Sign-up for a free GenIQ webcast: Click here.

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