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Activity Number: 608
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Learning and Data Science
Abstract #321367 View Presentation
Title: Sparsity-Oriented Importance Learning
Author(s): Chenglong Ye* and Yi Yang and Yuhong Yang
Companies: University of Minnesota and McGill University and University of Minnesota
Keywords: variable importance ; Model mixing ; Model selection

Model importance of variables in a dataset has attracted much attention in recent years. This paper proposes a new variable importance measure( SOIL) to address the issue, by the method of model mixing . Then we demonstrate the propeties of SOIL importance in contrast to other importance measures using several simulation models. Also we study two real data examples Colon cancer data and BGSboys date to provide some new insight of the SOIL importance.

Authors who are presenting talks have a * after their name.

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