JSM 2004 - Toronto

Abstract #300299

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Activity Number: 361
Type: Invited
Date/Time: Wednesday, August 11, 2004 : 2:00 PM to 3:50 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #300299
Title: Variable Selection for Prediction Where There are an Excessive Number of Variables
Author(s): Jack Liu*+ and S. Stanley Young
Companies: NISS and NISS
Address: PO Box 14009, RTP, NC, 27709,
Keywords: variable selection ; n< ; over-determined systems ; prediction
Abstract:

Assay systems are now available where a very large number of descriptors are available for each sample. For microarrays and proteomics there can be tens of thousands of descriptors. New methods of assay for metabolites can give quantitative values for thousands of descriptors. Often there are only tens or a few hundred samples where we want to predict some characteristic of the sample, tumor versus normal or diseased versus normal. Predictions can be made using linear combinations of large numbers of predictors or by focusing on small sets of predictors. There is a need to have interpretable decision rules so we will focus on small sets of predictors in trying to understand these complex datasets. We use a microarray and a metabolic dataset to demonstrate our methods.

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