Optimization of approximate decision rules relative to number of misclassifications: Comparison of greedy and dynamic programming approaches

Handle URI:
http://hdl.handle.net/10754/564643
Title:
Optimization of approximate decision rules relative to number of misclassifications: Comparison of greedy and dynamic programming approaches
Authors:
Amin, Talha ( 0000-0003-3035-8612 ) ; Chikalov, Igor; Moshkov, Mikhail ( 0000-0003-0085-9483 ) ; Zielosko, Beata
Abstract:
In the paper, we present a comparison of dynamic programming and greedy approaches for construction and optimization of approximate decision rules relative to the number of misclassifications. We use an uncertainty measure that is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. Experimental results with decision tables from the UCI Machine Learning Repository are also presented. © 2013 Springer-Verlag.
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:
Knowledge Engineering, Machine Learning and Lattice Computing with Applications
Conference/Event name:
16th International Conference on Knowledge Engineering, Machine Learning and Lattice Computing with Applications, KES 2012
Issue Date:
2013
DOI:
10.1007/978-3-642-37343-5_5
Type:
Conference Paper
ISSN:
03029743
ISBN:
9783642373428
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.authorAmin, Talhaen
dc.contributor.authorChikalov, Igoren
dc.contributor.authorMoshkov, Mikhailen
dc.contributor.authorZielosko, Beataen
dc.date.accessioned2015-08-04T07:10:40Zen
dc.date.available2015-08-04T07:10:40Zen
dc.date.issued2013en
dc.identifier.isbn9783642373428en
dc.identifier.issn03029743en
dc.identifier.doi10.1007/978-3-642-37343-5_5en
dc.identifier.urihttp://hdl.handle.net/10754/564643en
dc.description.abstractIn the paper, we present a comparison of dynamic programming and greedy approaches for construction and optimization of approximate decision rules relative to the number of misclassifications. We use an uncertainty measure that is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. Experimental results with decision tables from the UCI Machine Learning Repository are also presented. © 2013 Springer-Verlag.en
dc.publisherSpringer Science + Business Mediaen
dc.subjectdecision rulesen
dc.subjectdynamic programming algorithmen
dc.subjectgreedy algorithmen
dc.subjectnumber of misclassificationsen
dc.titleOptimization of approximate decision rules relative to number of misclassifications: Comparison of greedy and dynamic programming approachesen
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.journalKnowledge Engineering, Machine Learning and Lattice Computing with Applicationsen
dc.conference.date10 September 2012 through 12 September 2012en
dc.conference.name16th International Conference on Knowledge Engineering, Machine Learning and Lattice Computing with Applications, KES 2012en
dc.conference.locationSan Sebastianen
dc.contributor.institutionInstitute of Computer Science, University of Silesia, 39, Bȩdzińska St., 41-200 Sosnowiec, Polanden
kaust.authorChikalov, Igoren
kaust.authorMoshkov, Mikhailen
kaust.authorZielosko, Beataen
kaust.authorAmin, Talhaen
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