JSM 2005 Online Program

JSM Activity #CE_31T

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

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CE_31T	Wed, 8/10/05, 10:00 AM - 11:45 AM	MCC-L100 C
Introduction to MARS: Predictive Modeling with Non-linear Automated Regression Tools - Continuing Education - CTW
ASA
Instructor(s): Dan Steinberg, Salford Systems, Mikhail Golovnya, Salford Systems
This tutorial introduces the main concepts behind Jerome Friedman's MARS, a modern regression tool that can help analysts quickly develop superior predictive models. MARS is a non-linear automated regression tool that can trace out any pattern detected in the data. MARS automates the model specification search, including variable selection, variable transformation, interaction detection, missing value handling, and model validation. Conventional regression models typically fit straight lines to data. Although this usually oversimplifies the data structure, the approximation is sometimes good enough for practical purposes. However, in the frequent situations in which a straight line is inappropriate, an expert modeler must search tediously for transformations to find the right curve. MARS approaches model construction more flexibly, allowing for bends, thresholds, and other departures from straight lines from the beginning. Attendees will be presented with the key benefits over conventional regression tools and over a modelers' tedious search for transformations to find the right curve. Attendees will see examples of how this data mining tool is used for real-world data analysis. Prerequisites: This course is intended to be accessible to anyone with experience with regression modeling.