An oversampling method for imbalanced data based on spatial distribution of minority samples sd-kmsmote

HIGHLIGHTS

  • who: Wensheng Yang from the Nanjing University have published the article: An oversampling method for imbalanced data based on spatial distribution of minority samples SD-KMSMOTE, in the Journal: Scientific Reports Scientific Reports
  • what: Inspired by Ref26, this study proposes an imbalanced data oversampling method, SD-KMSMOTE, based on the spatial distribution of minority samples. The authors evaluate the good performance of an oversampling method by combining the classification algorithms. To verify the performance of the proposed method in this study with datasets of different balancing rates, SMOTE is introduced as a comparison group in . . .

     

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