"Whatever you are able to do with your might, do it."

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, i.e., of identifying upper performing individuals often displayed in a decile table. GenIQ models outdo statistical models, due to its unique equation and supplemental output. Moreover, GenIQ provides a book load of machine-learning data mining techniques for better predictive modeling and analysis of big data.

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Machine-learning Predictive Modeling & Data Mining are fully furnished in the GenIQ Model software, which explicitly maximizes expected response or profit - as displayed in a decile table - from direct-/database-/tele-marketing solicitations, marketing-mix optimization programs, business-intelligent offerings, CRM campaigns, web-/email-based broadcasts, and the like. The GenIQ Model is a flexible assumption-free, nonparametric model based on the machine learning paradigm of genetic programming. The GenIQ-Response and GenIQ-Profit modules offer a clear advantage over "inflexible" logistic and ordinary regression methods, whose performance is based on theoretical assumptions, a pre-specified parametric model, and data restrictions. Enroll in a free GenIQ Model Webcast.

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