A highly adaptive oversampling approach to address the issue of data imbalance

HIGHLIGHTS

• who: Szeghalmy Szilvia and Fazekas Attila from the (UNIVERSITY) have published the paper: A Highly Adaptive Oversampling Approach to Address the Issue of Data Imbalance, in the Journal: Computers 2022, 11, 73. of /2022/
• what: In the rest of this paper, the authors focus primarily on the oversampling algorithms (excluding deep-learning-based solutions). If the authors compare Figure 1a to Figure 2a, the authors can see that the decision boundary has shifted due to noise. The variant used in this study determines the weight of a minority sample x according to the following formula . . .
  

   

  

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