Using Artificial Intelligence for Model Selection

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dc.creatorGoldstein, Darin
dc.creatorMurray, William
dc.creatorYang, Binh
dc.date2003-10-05
dc.date.accessioned2026-07-07T03:20:24Z
dc.date.available2026-07-07T03:20:24Z
dc.descriptionWe apply the optimization algorithm Adaptive Simulated Annealing (ASA) to the problem of analyzing data on a large population and selecting the best model to predict that an individual with various traits will have a particular disease. We compare ASA with traditional forward and backward regression on computer simulated data. We find that the traditional methods of modeling are better for smaller data sets whereas a numerically stable ASA seems to perform better on larger and more complicated data sets.
dc.description10 pages, no figures, in Proceedings, Hawaii International Conference on Statistics and Related Fields, June 5-8, 2003
dc.identifierhttps://arxiv.org/abs/cs/0310005
dc.identifierhttp://arxiv.org/abs/cs/0310005
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31812
dc.subjectArtificial Intelligence
dc.subjectQuantitative Methods
dc.subjectH.2.8; J.3
dc.titleUsing Artificial Intelligence for Model Selection
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