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Attribute Reduction of Incomplete Information Systems: An Intuitionistic Fuzzy Rough Set Approach

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Recent Advances in Intelligent Information Systems and Applied Mathematics (ICITAM 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 863))

Abstract

Nowadays, fast expansion of data processing tools leads to increase in databases in terms of objects as well as attributes in different fields like image processing, pattern recognition and risk prediction in management. Attribute reduction is a process of selecting those attributes that are mutually sufficient and individually necessary for retaining basic property of the given information system. In this paper, we introduce a novel approach for attribute reduction of an incomplete information system based on intuitionistic fuzzy rough set theory. We define an intuitionistic fuzzy tolerance relation between two objects and calculate rough approximations of an incomplete information space by using tolerance classes of each object. The degree of dependency method is used for calculating reduct set of an incomplete information system in order to handle noise and irrelevant data. An algorithm is presented for better understanding of the proposed approach and is applied to an incomplete information system. Finally, we compare proposed approach with an existing approach for attribute reduction of an incomplete information system through an example.

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Acknowledgement

First author wish to acknowledge CSIR, India for funding.

Author information

Authors and Affiliations

  1. DST-Centre for Interdisciplinary Mathematical Sciences, Institute of Science, BHU, Varanasi, 221005, India

    Shivani Singh

  2. Department of Mathematics, SBAS, Galgotias University, Gautam Buddha Nagar, Greater Noida, 201310, UP, India

    Shivam Shreevastava & Tanmoy Som

Authors
  1. Shivani Singh
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  2. Shivam Shreevastava
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  3. Tanmoy Som
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Corresponding author

Correspondence to Shivam Shreevastava .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  2. Haldia Institute of Technology, Haldia, West Bengal, India

    Dipak Kumar Jana

  3. Maulana Abul Kalam Azad University of Technology, Haringhata, India

    Debasis Giri

  4. Haldia Institute of Technology, Haldia, India

    Arif Ahmed

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Singh, S., Shreevastava, S., Som, T. (2020). Attribute Reduction of Incomplete Information Systems: An Intuitionistic Fuzzy Rough Set Approach. In: Castillo, O., Jana, D., Giri, D., Ahmed, A. (eds) Recent Advances in Intelligent Information Systems and Applied Mathematics. ICITAM 2019. Studies in Computational Intelligence, vol 863. Springer, Cham. https://doi.org/10.1007/978-3-030-34152-7_48

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