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dc.contributor.authorAzad, Mohammad
dc.contributor.authorChikalov, Igor
dc.contributor.authorMoshkov, Mikhail
dc.date.accessioned2015-08-04T07:11:30Z
dc.date.available2015-08-04T07:11:30Z
dc.date.issued2013
dc.identifier.isbn9783642412172
dc.identifier.issn03029743
dc.identifier.doi10.1007/978-3-642-41218-9_6
dc.identifier.urihttp://hdl.handle.net/10754/564665
dc.description.abstractIn inconsistent decision tables, there are groups of rows with equal values of conditional attributes and different decisions (values of the decision attribute). We study three approaches to deal with such tables. Instead of a group of equal rows, we consider one row given by values of conditional attributes and we attach to this row: (i) the set of all decisions for rows from the group (many-valued decision approach); (ii) the most common decision for rows from the group (most common decision approach); and (iii) the unique code of the set of all decisions for rows from the group (generalized decision approach). We present experimental results and compare the depth, average depth and number of nodes of decision trees constructed by a greedy algorithm in the framework of each of the three approaches. © 2013 Springer-Verlag.
dc.publisherSpringer Science + Business Media
dc.subjectBoundary Subtables
dc.subjectDecision Trees
dc.subjectGreedy Algorithms
dc.subjectInconsistent Decision Tables
dc.titleThree approaches to deal with inconsistent decision tables - Comparison of decision tree complexity
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.journalRough Sets, Fuzzy Sets, Data Mining, and Granular Computing
dc.conference.date11 October 2013 through 14 October 2013
dc.conference.name14th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2013
dc.conference.locationHalifax, NS
kaust.personAzad, Mohammad
kaust.personChikalov, Igor
kaust.personMoshkov, Mikhail


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