Comparison of greedy algorithms for α-decision tree construction

Handle URI:
http://hdl.handle.net/10754/564329
Title:
Comparison of greedy algorithms for α-decision tree construction
Authors:
Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail ( 0000-0003-0085-9483 )
Abstract:
A comparison among different heuristics that are used by greedy algorithms which constructs approximate decision trees (α-decision trees) is presented. The comparison is conducted using decision tables based on 24 data sets from UCI Machine Learning Repository [2]. Complexity of decision trees is estimated relative to several cost functions: depth, average depth, number of nodes, number of nonterminal nodes, and number of terminal nodes. Costs of trees built by greedy algorithms are compared with minimum costs calculated by an algorithm based on dynamic programming. The results of experiments assign to each cost function a set of potentially good heuristics that minimize it. © 2011 Springer-Verlag.
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
Publisher:
Springer Science + Business Media
Journal:
Rough Sets and Knowledge Technology
Conference/Event name:
6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011
Issue Date:
2011
DOI:
10.1007/978-3-642-24425-4_25
Type:
Conference Paper
ISSN:
03029743
ISBN:
9783642244247
Appears in Collections:
Conference Papers; 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.accessioned2015-08-04T06:23:52Zen
dc.date.available2015-08-04T06:23:52Zen
dc.date.issued2011en
dc.identifier.isbn9783642244247en
dc.identifier.issn03029743en
dc.identifier.doi10.1007/978-3-642-24425-4_25en
dc.identifier.urihttp://hdl.handle.net/10754/564329en
dc.description.abstractA comparison among different heuristics that are used by greedy algorithms which constructs approximate decision trees (α-decision trees) is presented. The comparison is conducted using decision tables based on 24 data sets from UCI Machine Learning Repository [2]. Complexity of decision trees is estimated relative to several cost functions: depth, average depth, number of nodes, number of nonterminal nodes, and number of terminal nodes. Costs of trees built by greedy algorithms are compared with minimum costs calculated by an algorithm based on dynamic programming. The results of experiments assign to each cost function a set of potentially good heuristics that minimize it. © 2011 Springer-Verlag.en
dc.publisherSpringer Science + Business Mediaen
dc.subjectDecision treeen
dc.subjectdynamic programmingen
dc.subjectgreedy algorithmen
dc.titleComparison of greedy algorithms for α-decision tree constructionen
dc.typeConference Paperen
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.journalRough Sets and Knowledge Technologyen
dc.conference.date9 October 2011 through 12 October 2011en
dc.conference.name6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011en
dc.conference.locationBanff, ABen
kaust.authorChikalov, Igoren
kaust.authorMoshkov, Mikhailen
kaust.authorAlkhalid, Abdulazizen
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