JSM 2015 Preliminary Program

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Legend: Washington State Convention Center = CC, Sheraton Seattle = S, Grand Hyatt = GH and The Conference Center = TCC
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CE_15C Mon, 8/10/2015, 8:30 AM - 5:00 PM S-Grand Ballroom B
Classification and Regression Trees and Forests (ADDED FEE) — Professional Development Continuing Education Course
ASA
It is more than 50 and 30 years since AID (Morgan and Sonquist 1963) and CART (Breiman et al 1984) appeared. Rapidly increasing use of trees among practitioners has led to great advances in algorithmic research over the last two decades. Modern tree models have higher prediction accuracy and do not have selection bias. They can fit linear models in the nodes using GLM, quantile, and other loss functions; response variables may be multivariate, longitudinal, or censored; and classification trees can employ linear splits and fit kernel and nearest-neighbor node models. This course begins with examples to compare tree and traditional models. Then it reviews the major algorithms, including AID, CART, C4.5, CHAID, CRUISE, CTREE, GUIDE, M5, MOB, and QUEST. Real data are used to illustrate the features of each, and results on prediction accuracy and model complexity versus forests and some machine learning methods are presented. Examples are drawn from business, science, and industry and include applications to subgroup identification for personalized medicine, missing value imputation in surveys, and differential item functioning in educational testing. Relevant software is mentioned where appropriate. Attendees should be familiar with multivariate analysis at the level of Johnson and Wichern's "Applied Multivariate Statistical Analysis."
Instructor(s): Wei-Yin Loh, University of Wisconsin




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