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Journal of Henan Normal University(Natural Science Edition). Core
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(Accepted Version) Online First Publishing Date: 2023-06-27 11:54:01

Multilabel feature selection algorithm using ReliefF and mRMRChinese Full TextEnglish Full Text (MT)

Sun Lin;Xu Feng;Li Shuo;Wang Zhen;

Abstract: The correlation between feature and label set is not deeply considered by existing multilabel feature selection models, which results in low classification accuracy. To address the issues, this paper proposed a multilabel feature selection method using ReliefF and maximum Relevance and Minimum Redundancy（mRMR）. Firstly, based on the mutual information, the correlation degree between the label and the label-set was defined. A new label weighting was constructed by calculating the proportion of th... More
Keywords：

multilabel learning; feature selection; label weighting; ReliefF; mRMR;

  • Series：

    (I) Electronic Technology ＆ Information Science

  • Subject：

    Automation Technology

  • Classification Code：

    TP18

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