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A graph approach to generate all possible regression submodels |
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| Authors: | Cristian Gatu Petko I Yanev Erricos J Kontoghiorghes |
| Affiliation: | a Institut d’informatique, Université de Neuchâtel, Switzerland b INRIA/IRISA, Rennes, France c Department of Public and Business Administration, University of Cyprus, Cyprus d Faculty of Computer Science, “Alexandru Ioan Cuza” University of Iasi, Romania e Faculty of Mathematics and Informatics, University of Plovdiv “Paisii Hilendarski,” Bulgaria f School of Computer Science and Information Systems, Birkbeck College, UK |
| 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. |
| Keywords: | Graphs Regression trees Model selection Combinatorial algorithms |
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