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


Performance Management: Improve It via Machine Learning
Bruce Ratner, Ph.D.

Understanding the factors (key drivers) that affect your organization’s performance, you are in a mighty position for managing your organization for performance improvement. The traditional statistical analysis and modeling is limited inherently as it does not have data mining muscle to dig into the data of even the modest size organization to produce the necessary analytical strategy for: uncovering the rootage of performance issues, identifying business opportunities, nourishing profitable growth.

The purpose of this article is to present a machine learning approach – the GenIQ Model© – that has the data mining muscle for digging into massive data to extract the needed analytical strategic. The GenIQ Model is a machine learning alternative model to the statistical regression model that lets the data define the model – automatically data mines for new variables, performs variable selection, and then specifies the model equation. GenIQ, exclusive of statistical regression’s imposed data restrictions, assumptions, and pre-specified form, clearly offers a superior approach for uncovering, identifying and nourishing the key drivers of performance improvement.

For more information about this article, call me at 516.791.3544, or e-mail, br@dmstat1.com.
My publisher owns the copyright of the article, about which this abstract addresses. The article will appear in my forthcoming book.
My publisher has granted me permission to discuss orally the article's content, but by no means provide an outline, draft or proof-ready of the article.


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