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Tolerance Rough Fuzzy Approximation Operators and Their Properties

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Machine Learning and Cybernetics (ICMLC 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 481))

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Abstract

In the framework of classification, the rough fuzzy set (RFS) deal with the fuzzy decision tables with discrete conditional attributes and fuzzy decision attribute. However, in many applications, the conditional attributes are often real-valued. In order to deal with this problem, this paper extends the RFS model to tolerance RFS, The definitions of the tolerance rough fuzzy set approximation operators are given, and their properties are investigated.

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Correspondence to Junhai Zhai .

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Zhang, Y., Zhai, J., Zhang, S. (2014). Tolerance Rough Fuzzy Approximation Operators and Their Properties. In: Wang, X., Pedrycz, W., Chan, P., He, Q. (eds) Machine Learning and Cybernetics. ICMLC 2014. Communications in Computer and Information Science, vol 481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45652-1_38

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  • DOI: https://doi.org/10.1007/978-3-662-45652-1_38

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45651-4

  • Online ISBN: 978-3-662-45652-1

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