A graph approach to generate all possible regression submodels
Gatu, C. and Yanev, P.I. and Kontoghiorghes, Erricos J. (2007) A graph approach to generate all possible regression submodels. Computational Statistics & Data Analysis 52 (2), 799 - 815. ISSN 0167-9473.
Abstract
A regression graph to enumerate and evaluate all possible subset regression models is introduced. The graph is a generalization of a regression tree. All the spanning trees of the graph are minimum spanning trees and provide an optimal computational procedure for generating all possible submodels. Each minimum spanning tree has a different structure and characteristics. An adaptation of a branch-and-bound algorithm which computes the best-subset models using the regression graph framework is proposed. Experimental results and comparison with an existing method based on a regression tree are presented and discussed.
Metadata
Item Type: | Article |
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Keyword(s) / Subject(s): | Graphs, regression trees, model selection, combinatorial algorithms |
School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
Depositing User: | Administrator |
Date Deposited: | 08 Aug 2011 13:04 |
Last Modified: | 09 Aug 2023 12:30 |
URI: | https://eprints.bbk.ac.uk/id/eprint/3967 |
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