research-article

Multi-confidence rule acquisition oriented attribute reduction of covering decision systems via combinatorial optimization

Authors:

Jinhai LiAuthors Info & Claims

Knowledge-Based Systems, Volume 50, Issue C

Pages 187 - 197

Published: 01 September 2013 Publication History

Abstract

Rule acquisition is one of the most concerned issues in the study of decision systems including covering decision systems. Usually, a covering decision system is inconsistent, which can lead to the result that some of the rules derived from the system are not certain but possible rules. Considering the fact that, in addition to the certain rules, the possible rules with high confidence are also commonly used in practice for making decision, and the compact rules without redundant conditional attributes can conveniently be used by a decision maker, we propose in this study a rule confidence preserving attribute reduction approach in order to extract from a covering decision system both the compact certain rules and the compact possible rules with their confidence degree being not less than a pre-specified threshold value. Furthermore, a combinatorial optimization algorithm is formulated to compute all the reducts. Some numerical experiments are further conducted to evaluate the performance of the proposed reduction method.

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Cited By

Zhang XLi JLi W(2022)A new mechanism of rule acquisition based on covering rough setsApplied Intelligence10.1007/s10489-021-03067-x52:11(12369-12381)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s10489-021-03067-x
Yang YChen DZhang XJi Z(2022)Covering rough set-based incremental feature selection for mixed decision systemSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-021-06687-026:6(2651-2669)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s00500-021-06687-0
Choromański MGrześ THońko P(2020)Breadth search strategies for finding minimal reducts: towards hardware implementationNeural Computing and Applications10.1007/s00521-020-04833-732:18(14801-14816)Online publication date: 19-Mar-2020
https://dl.acm.org/doi/10.1007/s00521-020-04833-7
Show More Cited By

Index Terms

Multi-confidence rule acquisition oriented attribute reduction of covering decision systems via combinatorial optimization
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
2. Theory of computation
  1. Logic

Index terms have been assigned to the content through auto-classification.

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cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 50, Issue C

September 2013

296 pages

ISSN:0950-7051

Issue’s Table of Contents

Copyright © Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 September 2013

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Cited By

Zhang XLi JLi W(2022)A new mechanism of rule acquisition based on covering rough setsApplied Intelligence10.1007/s10489-021-03067-x52:11(12369-12381)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s10489-021-03067-x
Yang YChen DZhang XJi Z(2022)Covering rough set-based incremental feature selection for mixed decision systemSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-021-06687-026:6(2651-2669)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s00500-021-06687-0
Choromański MGrześ THońko P(2020)Breadth search strategies for finding minimal reducts: towards hardware implementationNeural Computing and Applications10.1007/s00521-020-04833-732:18(14801-14816)Online publication date: 19-Mar-2020
https://dl.acm.org/doi/10.1007/s00521-020-04833-7
Ding WWang JWang J(2016)A hierarchical-coevolutionary-MapReduce-based knowledge reduction algorithm with robust ensemble Pareto equilibriumInformation Sciences: an International Journal10.1016/j.ins.2016.01.035342:C(153-175)Online publication date: 10-May-2016
https://dl.acm.org/doi/10.1016/j.ins.2016.01.035
Fan AZhao HZhu W(2016)Test-cost-sensitive attribute reduction on heterogeneous data for adaptive neighborhood modelSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-015-1770-x20:12(4813-4824)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1007/s00500-015-1770-x
Hońko P(2016)Attribute reductionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-014-1554-820:3(951-966)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1007/s00500-014-1554-8
Tan ALi JLin GLin Y(2015)Fast approach to knowledge acquisition in covering information systems using matrix operationsKnowledge-Based Systems10.1016/j.knosys.2015.02.00379:C(90-98)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.1016/j.knosys.2015.02.003
Chen JLi JLin YLin GMa Z(2015)Relations of reduction between covering generalized rough sets and concept latticesInformation Sciences: an International Journal10.1016/j.ins.2014.11.053304:C(16-27)Online publication date: 20-May-2015
https://dl.acm.org/doi/10.1016/j.ins.2014.11.053
Choromański MGrześ THońko P(undefined)Two FPGA Devices in the Problem of Finding Minimal ReductsComputer Information Systems and Industrial Management10.1007/978-3-030-28957-7_34(410-420)
https://dl.acm.org/doi/10.1007/978-3-030-28957-7_34

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