A Robust Classifier for Imbalanced Datasets

@inproceedings{Kang2014ARC,
  title={A Robust Classifier for Imbalanced Datasets},
  author={Sori Kang and Kotagiri Ramamohanarao},
  booktitle={PAKDD},
  year={2014}
}
Imbalanced dataset classification is a challenging problem, since many classifiers are sensitive to class distribution so that the classifiers’ prediction has bias towards majority class. Hellinger Distance has been proven that it is skew-insensitive and the decision trees that employ Hellinger Distance as a splitting criterion have shown better performance than other decision trees based on Information Gain. We propose a new decision tree induction classifier (HeDEx) based on Hellinger… CONTINUE READING