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WORLDCOMP'09 Tutorial: Dr. Dan Steinberg
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A Tour of Advanced Data Mining Methodologies
Dr. Dan Steinberg President and CEO of Salford Systems, Inc., San Diego, USA Date: July 15, 2009 Time: 6:00 - 9:30 PM Location: Ballroom 4 |
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Abstract
- CART, the classic decision tree
- MARS (multivariate adaptive regression splines), a flexible, highly automated regression technique
- TreeNet and RandomForests, which leverage the predictive power of CART models by combining a large number of trees together using either boosting or bootstrap aggregation approaches.
- Instructors wishing to learn more about data mining so they can include some coverage in their classes;
- Applied Statisticians wanting to learn new tools for exploratory and non-parametric data analysis; and,
- Researchers who have previously worked with data mining and have been mystified by earlier versions of the documentation and output.
Dr. Dan Steinberg, will discuss the classic CART (classification and regression trees) technique, as well as advanced data mining techniques recently developed by Stanford University Professor Jerome Friedman and University of California Professor Emeritus Leo Breiman. Methodologies and real-world applications will be presented for the following:
Objectives
To provide an introduction to and overview of Data Mining Analysis and to provide practical examples to assist attendees in conducting their own analyses.
Intended Audience
Biography of Instructor
Dan Steinberg, the President and CEO of Salford Systems, founded the company in 1983 just after receiving his Ph.D. in Economics at Harvard.
He has also served as Assistant Professor of Economics at the University of California, San Diego, and participated in dozens of consulting projects for Fortune 100 clients. Dr. Steinberg has published articles in statistics, econometrics, computer science, and marketing journals, and has been a featured data mining issues speaker for the American Marketing Association, the American Statistical Association, the Direct Marketing Association and the Casualty Actuarial Society.
