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A Determining Degree-Based Method for Classification Problems with Interval-Valued Attributes

Author

Listed:
  • Xueyan Xu

    (Beijing Normal University)

  • Fusheng Yu

    (Beijing Normal University)

  • Runjun Wan

    (Liaoning Technical University)

Abstract

The determining degree-based classification methods, new types of classification methods built in the frame of factor space theory, mainly include factorial analysis, improved factorial analysis and set subtraction and rotation calculation (S&R). This paper first compares the three methods to present a comprehensive understanding of them and claims that whether to reuse dominant factors and to use synthetic partitioning are the main differences between factorial analysis and S&R. Furthermore, this paper introduces S&R definitively and concisely through an example. Based on the investigation, we propose a novel method for classification problems with interval-valued attributes that uses a determining degree to discretize interval values, and takes S&R as one of its steps. Experimental results show that this method is effective and reasonable.

Suggested Citation

  • Xueyan Xu & Fusheng Yu & Runjun Wan, 2023. "A Determining Degree-Based Method for Classification Problems with Interval-Valued Attributes," Annals of Data Science, Springer, vol. 10(2), pages 393-413, April.
    • Handle: RePEc:spr:aodasc:v:10:y:2023:i:2:d:10.1007_s40745-022-00387-8
    DOI: 10.1007/s40745-022-00387-8
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    References listed on IDEAS

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    1. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
    2. Peizhuang Wang & He Ouyang & Yixin Zhong & Huacan He, 2016. "Cognition Math Based on Factor Space," Annals of Data Science, Springer, vol. 3(3), pages 281-303, September.
    3. Feng Liu & Yong Shi, 2020. "Investigating Laws of Intelligence Based on AI IQ Research," Annals of Data Science, Springer, vol. 7(3), pages 399-416, September.
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