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dc.contributor.authorAzad, Mohammad
dc.contributor.authorMoshkov, Mikhail
dc.date.accessioned2015-12-01T13:56:29Z
dc.date.available2015-12-01T13:56:29Z
dc.date.issued2015-10-11
dc.identifier.doi10.15439/2015F231
dc.identifier.urihttp://hdl.handle.net/10754/583064
dc.description.abstractDecision tree is a widely used technique to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples (objects) with equal values of conditional attributes but different decisions (values of the decision attribute), then to discover the essential patterns or knowledge from the data set is challenging. We consider three approaches (generalized, most common and many-valued decision) to handle such inconsistency. We created different greedy algorithms using various types of impurity and uncertainty measures to construct decision trees. We compared the three approaches based on the decision tree properties of the depth, average depth and number of nodes. Based on the result of the comparison, we choose to work with the many-valued decision approach. Now to determine which greedy algorithms are efficient, we compared them based on the optimization and classification results. It was found that some greedy algorithms Mult\_ws\_entSort, and Mult\_ws\_entML are good for both optimization and classification.
dc.publisherPolish Information Processing Society PTI
dc.relation.urlhttps://fedcsis.org/proceedings/2015/drp/231.html
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.titleClassification and Optimization of Decision Trees for Inconsistent Decision Tables Represented as MVD Tables
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalProceedings of the 2015 Federated Conference on Computer Science and Information Systems
dc.conference.dateSeptember 13–16, 2015
dc.conference.nameAnnals of Computer Science and Information Systems, Volume 5
dc.conference.locationŁódź, Poland
dc.eprint.versionPost-print
kaust.personAzad, Mohammad
kaust.personMoshkov, Mikhail
refterms.dateFOA2018-06-13T11:38:44Z


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