Using Artificial Intelligence for Model Selection
Artificial Intelligence
2007-05-23 v1 Quantitative Methods
Abstract
We 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.
Cite
@article{arxiv.cs/0310005,
title = {Using Artificial Intelligence for Model Selection},
author = {Darin Goldstein and William Murray and Binh Yang},
journal= {arXiv preprint arXiv:cs/0310005},
year = {2007}
}
Comments
10 pages, no figures, in Proceedings, Hawaii International Conference on Statistics and Related Fields, June 5-8, 2003