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Roughness measure based on description ability for attribute reduction in information system

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Abstract

As a quantitative index of processing uncertain information by rough set theory, roughness measure is the basis of many decision-making problems such as resource management, system optimization etc. Therefore constructing roughness measure reflecting different decision preference has important theoretical and practical value. In this paper, we first analyze the characteristics and deficiencies of Pawlak roughness, and further propose the concepts of lower (upper) accuracy. We second establish an description ability-based roughness measure (DRD) by combining with two basic measure factors-lower (upper) accuracy. We third analyze the characteristics of DRD and further give some sufficient and necessary conditions. Finally, we propose a DRD-based reduction method (DRD-RM), and discuss the difference and relation between DRD-RM and the existing reduction methods by experimental analysis for UCI data. The experimental results show that DRD-RM is an effective technique.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (71771078, 71371064), the Scientific Research Project Item of the Hebei Province Education Office (QN2017068), and the Natural Science Foundation of Hebei Province (F2015208100, F2015208099, F2016208092).

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Authors and Affiliations

  1. School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang, 050018, China

    Fachao Li & Chenxia Jin

  2. EBUPT Information Technology Co., Ltd., Beijing, 100000, China

    Jinning Yang

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  1. Fachao Li
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  2. Chenxia Jin
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  3. Jinning Yang
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Correspondence to Chenxia Jin.

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Li, F., Jin, C. & Yang, J. Roughness measure based on description ability for attribute reduction in information system. Int. J. Mach. Learn. & Cyber. 10, 925–934 (2019). https://doi.org/10.1007/s13042-017-0771-8

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  • DOI: https://doi.org/10.1007/s13042-017-0771-8

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