JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2023, Vol. 58 ›› Issue (5): 26-35.doi: 10.6040/j.issn.1671-9352.4.2022.1581

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Attribute reduction algorithm based on discreteness of the universe

LIU Changshun1, LIU Yan1, SONG Jingjing1*, XU Taihua1,2   

  1. 1. School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, Jiangsu, China;
    2. Key Laboratory of Oceanographic Big Data Mining &
    Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China
  • Published:2023-05-15

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Abstract: A fitness function based on the dispersion of the universe was proposed. Under the forward greedy searching strategy, the fitness function was employed to evaluate the importance of conditional attributes and then used to derive the reduct of the neighborhood rough set. The proposed algorithm was compared with three state-of-the-art attribute reduction algorithms and validated on 12 UCI datasets. Experimental results showed that compared with the other three algorithms, the proposed algorithm exhibited better in time consumption and stability without reducing the classification effect.

Key words: attribute reduction, conditional attribute, fitness function, neighborhood rough set

CLC Number: 

  • TP181
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