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Title: A graph approach to generate all possible regression submodels
Authors: Gatu, Cristian 
Yanev, Petko I. 
Kontoghiorghes, Erricos John 
Keywords: Regression analysis;Algorithms;Branch-and-bound algorithm;Computer simulation;Set theory
Issue Date: 2007
Publisher: Elsevier
Source: Computational Statistics and Data Analysis, 2007, Volume 52, Issue 2, Pages 799-815
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.
ISSN: 01679473
Rights: © 2007 Elsevier B.V. All rights reserved.
Type: Article
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