A tool for study of optimal decision trees

Handle URI:
http://hdl.handle.net/10754/564245
Title:
A tool for study of optimal decision trees
Authors:
Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail ( 0000-0003-0085-9483 )
Abstract:
The paper describes a tool which allows us for relatively small decision tables to make consecutive optimization of decision trees relative to various complexity measures such as number of nodes, average depth, and depth, and to find parameters and the number of optimal decision trees. © 2010 Springer-Verlag Berlin Heidelberg.
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 Set and Knowledge Technology
Conference/Event name:
5th International Conference on Rough Set and Knowledge Technology, RSKT 2010
Issue Date:
2010
DOI:
10.1007/978-3-642-16248-0_51
Type:
Conference Paper
ISSN:
03029743
ISBN:
3642162479; 9783642162473
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.accessioned2015-08-04T06:20:32Zen
dc.date.available2015-08-04T06:20:32Zen
dc.date.issued2010en
dc.identifier.isbn3642162479; 9783642162473en
dc.identifier.issn03029743en
dc.identifier.doi10.1007/978-3-642-16248-0_51en
dc.identifier.urihttp://hdl.handle.net/10754/564245en
dc.description.abstractThe paper describes a tool which allows us for relatively small decision tables to make consecutive optimization of decision trees relative to various complexity measures such as number of nodes, average depth, and depth, and to find parameters and the number of optimal decision trees. © 2010 Springer-Verlag Berlin Heidelberg.en
dc.publisherSpringer Science + Business Mediaen
dc.subjectDecision treeen
dc.subjectdynamic programmingen
dc.subjectoptimizationen
dc.titleA tool for study of optimal decision treesen
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 Set and Knowledge Technologyen
dc.conference.date15 October 2010 through 17 October 2010en
dc.conference.name5th International Conference on Rough Set and Knowledge Technology, RSKT 2010en
dc.conference.locationBeijingen
kaust.authorChikalov, Igoren
kaust.authorMoshkov, Mikhailen
kaust.authorAlkhalid, Abdulazizen
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