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dc.contributor.authorAzad, Mohammad
dc.contributor.authorMoshkov, Mikhail
dc.date.accessioned2015-08-04T07:27:44Z
dc.date.available2015-08-04T07:27:44Z
dc.date.issued2014-10
dc.identifier.isbn9781479954643
dc.identifier.doi10.1109/GRC.2014.6982798
dc.identifier.urihttp://hdl.handle.net/10754/565000
dc.description.abstractIn this paper, we consider multi-label decision tables that have a set of decisions attached to each row. Our goal is to find one decision from the set of decisions for each row by using decision tree as our tool. Considering our target to minimize the depth of the decision tree, we devised various kinds of greedy algorithms as well as dynamic programming algorithm. 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 depth of decision trees.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectdecision tree
dc.subjectdepth
dc.subjectdynamic programming
dc.subjectgreedy algorithm
dc.subjectmulti-label decision table
dc.titleMinimization of decision tree depth for multi-label decision tables
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentExtensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Group
dc.identifier.journal2014 IEEE International Conference on Granular Computing (GrC)
dc.conference.date22 October 2014 through 24 October 2014
dc.conference.name2014 IEEE International Conference on Granular Computing, GrC 2014
kaust.personAzad, Mohammad
kaust.personMoshkov, Mikhail


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