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23 May 2023 An improved density peak clustering algorithm
Baobin Duan, Ping Wei, Weiyuan Ma
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Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 1260442 (2023) https://doi.org/10.1117/12.2674757
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China
Abstract
As the density peak clustering algorithm is insensitive to local structure, having bad clustering effect on data sets with uneven density distribution, and the algorithm does not take into account the hierarchy of data points, an improvement of density peak clustering algorithm is presented. The contribution factor is introduced into the local density calculation of data points to improve the insensitivity of the original algorithm to the local structure. In addition, the concept of trend is adopted to reduce the allocation joint error caused by the original algorithm only judging the similarity according to the distance of data points, and the method of leading forest is proposed to explain the hierarchy of data points. Finally, the experiments on artificial data sets and UCI datasets show that the improved algorithm is feasible.
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Baobin Duan, Ping Wei, and Weiyuan Ma "An improved density peak clustering algorithm", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 1260442 (23 May 2023); https://doi.org/10.1117/12.2674757
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KEYWORDS
Evolutionary algorithms
Iris
Structural design
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