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


Webcast for Demonstrating the GenIQ Model
Bruce Ratner, Ph.D.
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Subject: WEBCAST for Statistical Modelers and Data Miners: Demonstration of the GenIQ Model© - no charge!  
Date:     Mutually Convenient Date & Time
                  wcfb
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.GenIQ requires no programming, produces models that outdo statistical models, and is a different model: unsuspected equation, ungainly interpretation, and easy implementation.

Prerequisites for the GenIQ Webcast 
1. Entry-level/well-schooled modeler of statistical ordinary least squares and logistic regression models, AND who can think out of the box. 
OR
2Mid-level or Practiced-to-advanced modeler of statistical ordinary least squares and logistic regression models, AND who can think out of the box. 

GenIQ Webcasts are one-on-one
, you and your invited colleagues, and me.This allows for me to give you my full attention to answer all your questions, without feeling that you are taking-up other attendees' time. Please do not be put off by the webcast. It has proven to be the most effective way of my explaining the GenIQ Model. 

To Register for either webcast version
please anwser Question #1, below:
Version 1: The GenIQ Model Software Demonstration (30 minutes; must have an understanding of genetic programming (GP)).
Version 2: The GenIQ Model Presentation (90 minutes: GP theory-lite tutorial, not a sales-pitch presentation; and demonstration of software). 

The GenIQ Model Webcast is a perfect place to start if you want to perform better predictive modeling and data mining!!

Question #1. Please provide me with the following information by clicking email

  • Two dates & times available for the GenIQ Webcast
  • Statistical Modeling Experience:  1) Entry-level modeler .. , 2) Mid-level modeler .. , 3) Practiced-to-advanced modeler .. .  
  • GP Experience:                         1) None .. , 2) Have take a course that included GP .. , 3) Have a good understanding of GP .. .
  • Do you, at least in part, use the decile table/analysis to determine the best model? 1) Yes, or 2) No
  • I would like to attend 1) The GenIQ Model Software Demonstration, or 2) The GenIQ Model Presentation
  • Level of Ability-&-Atttitude of thinking out of the box on a scale of: 1) None, ... , 10) Always willing to consider new ideas.

Once we have agreed on a date & time, you will receive a "GoToMeeting© Invitation" email with instructions on how to join the event. 


I discuss:
  • Data basics: What kind of data is required for genetic modeling and data mining; in what format must the data be; what steps are necessary to prepare data appropriately (there are none!).
  • What kinds of questions can be answered with GenIQ data mining.
  • How GenIQ models work: The inputs, the outputs, and the nature of its predictive mechanism of GP.
  • Evaluation criteria: How GenIQ predictive models can be assessed and their value measured.  
I guarantee:
  • To show that 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. 

    Please do not hesitate to contact me if you have any questions.

    br
    Bruce Ratner, Ph.D.


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.