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dc.contributor.authorAlkhalid, Abdulaziz
dc.contributor.authorChikalov, Igor
dc.contributor.authorMoshkov, Mikhail
dc.date.accessioned2015-08-03T10:41:40Z
dc.date.available2015-08-03T10:41:40Z
dc.date.issued2013
dc.identifier.isbn9783642303401
dc.identifier.issn18684394
dc.identifier.doi10.1007/978-3-642-30341-8_3
dc.identifier.urihttp://hdl.handle.net/10754/562533
dc.description.abstractThis chapter is devoted to the study of 16 types of greedy algorithms for decision tree construction. The dynamic programming approach is used for construction of optimal decision trees. Optimization is performed relative to minimal values of average depth, depth, number of nodes, number of terminal nodes, and number of nonterminal nodes of decision trees. We compare average depth, depth, number of nodes, number of terminal nodes and number of nonterminal nodes of constructed trees with minimum values of the considered parameters obtained based on a dynamic programming approach. We report experiments performed on data sets from UCI ML Repository and randomly generated binary decision tables. As a result, for depth, average depth, and number of nodes we propose a number of good heuristics. © Springer-Verlag Berlin Heidelberg 2013.
dc.subjectDecision tree
dc.subjectdynamic programming
dc.subjectgreedy algorithms
dc.titleComparison of Greedy Algorithms for Decision Tree Optimization
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentExtensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Group
dc.identifier.journalIntelligent Systems Reference Library
kaust.personChikalov, Igor
kaust.personMoshkov, Mikhail
kaust.personAlkhalid, Abdulaziz


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