Abstract
In practice, we may obtain data which is set-valued due to the limitation of acquisition means or the requirement of practical problems. In this paper, we focus on how to reduce set-valued decision information systems under the disjunctive semantics. First, a new relation to measure the degree of similarity between two set-valued objects is defined, which overcomes the limitations of the existing measure methods. Second, an attribute reduction algorithm for set-valued decision information systems is proposed. At last, the experimental results demonstrate that the proposed method can simplify set-valued decision information systems and achieve higher classification accuracy than existing methods.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (61472056, 61533020, 61751312, 61379114), the Social Science Foundation of the Chinese Education Commission (15XJA630003), the Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJ1500416), Chongqing Research Program of Basic Research and Frontier Technology (cstc2017jcyjAX0406).
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Hu, J., Huang, S., Shao, R. (2018). Attribute Reduction of Set-Valued Decision Information System. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-319-91476-3_38
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DOI: https://doi.org/10.1007/978-3-319-91476-3_38
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