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    Optimization of decision rule complexity for decision tables with many-valued decisions

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    Type
    Conference Paper
    Authors
    Azad, Mohammad cc
    Chikalov, Igor
    Moshkov, Mikhail cc
    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
    Date
    2013-10
    Permanent link to this record
    http://hdl.handle.net/10754/564808
    
    Metadata
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    Abstract
    We describe new heuristics to construct decision rules for decision tables with many-valued decisions from the point of view of length and coverage which are enough good. We use statistical test to find leaders among the heuristics. After that, we compare our results with optimal result obtained by dynamic programming algorithms. The average percentage of relative difference between length (coverage) of constructed and optimal rules is at most 6.89% (15.89%, respectively) for leaders which seems to be a promising result. © 2013 IEEE.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2013 IEEE International Conference on Systems, Man, and Cybernetics
    Conference/Event name
    2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
    ISBN
    9780769551548
    DOI
    10.1109/SMC.2013.81
    ae974a485f413a2113503eed53cd6c53
    10.1109/SMC.2013.81
    Scopus Count
    Collections
    Conference Papers; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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