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


Webcast for Demonstrating the GenIQ Model
Bruce Ratner, Ph.D.
Live chat by Boldchat
Live chat by Boldchat

Subject: Webcast for Demonstration of the GenIQ Model - no charge! 
Date:     Wednesday, April 16, '08 1pm - 2:15pm (ET)

The GenIQ Model(c) 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. GenIQ requires no programming (though there is optional control of process), produces models that outdo statistical models, and is a different model: unsuspected equation, ungainly interpretation, and easy implementation.

Prerequisites for the GenIQ Webcast
1. A minimum of one year of building statistical ordinary least squares and logistic regression models, or an end-user of statistical regression models.
2. At least a nodding-acquaintance of the decile table/gains chart.

To Register for the Webcast
1. Please click this email link to register, and provide:
  • Name
  • Business email address
  • Telephone number
  • Company
  • Job function
  • Experience: a) Advanced, b) In-betweenie, c) Satisfy-the-prerequisites.
2. Once you have registered, you will receive a confirmation email message with instructions on how to join the event.

This 75 minute webcast is a perfect place to start if you want better predictive modeling and data mining!!

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 genetic programming.
  • 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.