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

Mohammad Azad; Igor Chikalov; Mikhail Moshkov

doi:10.1109/SMC.2013.81

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

Mohammad Azad, Igor Chikalov, Mikhail Moshkov

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

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.

Original language	English (US)
Title of host publication	2013 IEEE International Conference on Systems, Man, and Cybernetics
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	444-448
Number of pages	5
ISBN (Print)	9780769551548
DOIs	https://doi.org/10.1109/SMC.2013.81
State	Published - Oct 2013

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KAUST Repository Item: Exported on 2020-10-01

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10.1109/SMC.2013.81

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title = "Optimization of decision rule complexity for decision tables with many-valued decisions",

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. {\textcopyright} 2013 IEEE.",

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Optimization of decision rule complexity for decision tables with many-valued decisions. / Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail.
2013 IEEE International Conference on Systems, Man, and Cybernetics. Institute of Electrical and Electronics Engineers (IEEE), 2013. p. 444-448.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Optimization of decision rule complexity for decision tables with many-valued decisions

AU - Azad, Mohammad

AU - Chikalov, Igor

AU - Moshkov, Mikhail

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PY - 2013/10

Y1 - 2013/10

N2 - 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.

AB - 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.

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DO - 10.1109/SMC.2013.81

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BT - 2013 IEEE International Conference on Systems, Man, and Cybernetics

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

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

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