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The Improvement of Attribute Reduction Algorithm Based on Information Gain Ratio in Rough Set Theory

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Business Intelligence and Information Technology (BIIT 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 107))

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Abstract

Due to the various data sets and the cumbersome and diverse data types, there must be many redundant attributes in them, which greatly increases the classification time in the background of rough set theory. In this paper, we improve the attribute reduction algorithm by information gain ratio. The data sets obtained after the attribute reduction of this method are used for classification, and the data sets are directly used for classification and comparison with other common classification methods. Experimental data verify that the improved algorithm in this article is effective. It can improve the classification speed greatly and shorten the time spent.

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Acknowledgment

The author sincerely thanks the members of the research team for their joint efforts and the editors and reviewers for their valuable comments.

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Authors and Affiliations

  1. Harbin University of Commerce, Harbin, 150028, China

    Wenjing Wang, Min Guo, Tongtong Han & Shiyong Ning

  2. Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing, Harbin, 150028, China

    Shiyong Ning

Authors
  1. Wenjing Wang
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  2. Min Guo
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  3. Tongtong Han
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  4. Shiyong Ning
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Corresponding author

Correspondence to Shiyong Ning .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Yaoqun Xu

  3. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Zhijie Zhao

  4. Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

    Sabah Mohammed

  5. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Zhipeng Fan

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Wang, W., Guo, M., Han, T., Ning, S. (2022). The Improvement of Attribute Reduction Algorithm Based on Information Gain Ratio in Rough Set Theory. In: Hassanien, A.E., Xu, Y., Zhao, Z., Mohammed, S., Fan, Z. (eds) Business Intelligence and Information Technology. BIIT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 107. Springer, Cham. https://doi.org/10.1007/978-3-030-92632-8_15

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