JSM 2012 Online Program

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CE_12C	Mon, 7/30/2012, 8:00 AM - 12:00 PM	HQ-Indigo H
Nonlinear Regression and Ensemble Methods — Continuing Education Course
ASA , Section on Statistical Learning and Data Mining
Instructor(s): Bertrand Clarke, University of Miami
We will provide an overview of modeling for the purposes of prediction. We treat two common methods for nonlinear regression, neural networks and recursive partitioning, including estimation of parameters, model selection, and evaluation of performance. This is done primarily from a conceptual point of view illustrated by examples. Proceeding from looking at individual models we consider ensembles of models and use weighted averages of the predictions the models in the ensemble give. We present the main and emerging techniques for model averages and their main properties. We include comparisons of the methods and discussion of how to choose the models in the ensemble.

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