White Papers

Cross-Validation and Learning Curve Model Comparison With JMP Genomics and Grid Computing

Category: Data Management

Tags: cpu, computing, data

Overview The Food and Drug Administration has challenged researchers to demonstrate whether or not gene expression data can reliably predict future disease. JMP Genomics responded with a suite of predictive modeling tools suitable for short, fat data: tens of observations with tens of thousands of variables. The approach is to compare a variety of models, as one does not know a priori what is appropriate for a particular data set. The number of types and subtypes of models that are practical to consider is primarily limited by CPU time. SAS Grid Manager, in conjunction with JMP Genomics, provides the intelligent allocation of distributed computing resources and parallel application execution necessary to provide more accurate and timely predictive modeling.

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Publisher
SAS Institute
File Format
PDF
Date Published
May 29, 2009
Format
White Papers
Topics
High Performance Computing

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