Kde-based ensemble learning for imbalanced data

HIGHLIGHTS

• who: Firuz Kamalov and colleagues from the Department of Electrical Engineering, Canadian University Dubai, Dubai, United Arab Emirates Bosch AG, Stuttgart, Germany have published the paper: KDE-Based Ensemble Learning for Imbalanced Data, in the Journal: Electronics 2022, 11, 2703. of /2022/
• what: The authors propose a novel ensemble classification method designed to deal with imbalanced data. The authors show that the proposed method results in a lower variance of the model estimator. The authors evaluate the effectiveness of the proposed KDE-based ensemble classifier on several synthetic and real-life datasets. The aim of . . .
  

   

  

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