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dc.contributor.authorAzad, Mohammad
dc.contributor.authorMoshkov, Mikhail
dc.date.accessioned2015-04-27T13:57:28Z
dc.date.available2015-04-27T13:57:28Z
dc.date.issued2014-09-13
dc.identifier.citationMinimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions 2014, 35:368 Procedia Computer Science
dc.identifier.issn18770509
dc.identifier.doi10.1016/j.procs.2014.08.117
dc.identifier.urihttp://hdl.handle.net/10754/550702
dc.description.abstractThe paper is devoted to the analysis of greedy algorithms for the minimization of average depth of decision trees for decision tables such that each row is labeled with a set of decisions. The goal is to find one decision from the set of decisions. When we compare with the optimal result obtained from dynamic programming algorithm, we found some greedy algorithms produces results which are close to the optimal result for the minimization of average depth of decision trees.
dc.publisherElsevier BV
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1877050914010825
dc.rightsArchived with thanks to Procedia Computer Science. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/3.0/ ).
dc.subjectMany-valued decisions
dc.subjectOptimization
dc.subjectDecision Tree
dc.subjectDynamic Programming
dc.subjectGreedy Algorithm
dc.titleMinimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalProcedia Computer Science
dc.conference.date2014-09-15 to 2014-09-17
dc.conference.nameInternational Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2014
dc.conference.locationGdynia, POL
dc.eprint.versionPublisher's Version/PDF
kaust.personAzad, Mohammad
kaust.personMoshkov, Mikhail
refterms.dateFOA2018-06-13T17:27:33Z


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