Comparison of Greedy Algorithms for Decision Tree Optimization

Handle URI:
http://hdl.handle.net/10754/562533
Title:
Comparison of Greedy Algorithms for Decision Tree Optimization
Authors:
Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail ( 0000-0003-0085-9483 )
Abstract:
This 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Applied Mathematics and Computational Science Program; Extensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Group
Journal:
Intelligent Systems Reference Library
Issue Date:
2013
DOI:
10.1007/978-3-642-30341-8_3
Type:
Article
ISSN:
18684394
ISBN:
9783642303401
Appears in Collections:
Articles; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAlkhalid, Abdulazizen
dc.contributor.authorChikalov, Igoren
dc.contributor.authorMoshkov, Mikhailen
dc.date.accessioned2015-08-03T10:41:40Zen
dc.date.available2015-08-03T10:41:40Zen
dc.date.issued2013en
dc.identifier.isbn9783642303401en
dc.identifier.issn18684394en
dc.identifier.doi10.1007/978-3-642-30341-8_3en
dc.identifier.urihttp://hdl.handle.net/10754/562533en
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.en
dc.subjectDecision treeen
dc.subjectdynamic programmingen
dc.subjectgreedy algorithmsen
dc.titleComparison of Greedy Algorithms for Decision Tree Optimizationen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentApplied Mathematics and Computational Science Programen
dc.contributor.departmentExtensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Groupen
dc.identifier.journalIntelligent Systems Reference Libraryen
kaust.authorChikalov, Igoren
kaust.authorMoshkov, Mikhailen
kaust.authorAlkhalid, Abdulazizen
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