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A Method for Boundary Processing in Three-Way Decisions Based on Hierarchical Feature Representation

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Abstract

For binary classification problem, all samples can be divided into three regions based on the three-way decision theory: positive regions, negative regions and boundary regions. These samples in boundary regions may be impossible to make a definite decision for lacking of detailed information. More information obtained from positive and negative regions is crucial for boundary processing. In the real word, people may identify positive regions based on one rule, and identify negative regions on another. The samples in boundary regions are also divided to positive or negative regions based on different rules. In this paper, we propose a method for processing boundary regions in three-way decisions based on hierarchical feature representation (\(HFR-TWD\)), which can obtain hierarchical feature representation of positive and negative regions. Firstly, all samples are divided into three regions by MinCA, which builds the most accurate covers for each class. Then samples in positive regions and negative regions respectively construct hierarchical feature representation. Thirdly, the best feature representation of each class is selected by using boundary region validating. Finally, boundary samples in test set are divided according to best feature representation of each class. Experiments show that the proposed method \(HFR-TWD\) improves classification accuracy.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 61602003, 61673020, and 61402006), National High Technology Research and Development Program (863 Plan)(Grant #2015A-A124102), Innovation Zone Project Program for Science and Technology of China’s National Defense (Grant No. 2017-0001-863015-0009), the Provincial Natural Science Foundation of Anhui Province (Grant #1708085QF156), the Natural Science Foundation of Jiangsu Province (BK20170809), the China Postdoctoral Science Foundation (Grant No. 2018M632304).

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Authors and Affiliations

  1. School of Computer Science and Technology, Anhui University, Hefei, 230601, Anhui, People’s Republic of China

    Jie Chen, Yang Xu, Shu Zhao, Yuanting Yan, Yanping Zhang & Qianqian Wang

  2. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Weiwei Li

  3. Anhui Electrical Engineering Professional Technique College, Hefei, 230051, Anhui, People’s Republic of China

    Xiangyang Wang

Authors
  1. Jie Chen
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  2. Yang Xu
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  3. Shu Zhao
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  4. Yuanting Yan
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  5. Yanping Zhang
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  6. Weiwei Li
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  7. Qianqian Wang
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  8. Xiangyang Wang
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Corresponding author

Correspondence to Shu Zhao .

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Editors and Affiliations

  1. University of Warsaw, Warsaw, Poland

    Hung Son Nguyen

  2. Faculty of Information Technology, Vietnam National University, Hanoi, Vietnam

    Quang-Thuy Ha

  3. School of Information Science, Southwest Jiaotong University, Chengdu, China

    Tianrui Li

  4. Institute of Computer Science, University of Silesia, Sosnowiec, Poland

    Małgorzata Przybyła-Kasperek

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Chen, J. et al. (2018). A Method for Boundary Processing in Three-Way Decisions Based on Hierarchical Feature Representation. In: Nguyen, H., Ha, QT., Li, T., Przybyła-Kasperek, M. (eds) Rough Sets. IJCRS 2018. Lecture Notes in Computer Science(), vol 11103. Springer, Cham. https://doi.org/10.1007/978-3-319-99368-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-99368-3_10

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