Diversified Ensemble Classifiers for Highly Imbalanced Data Learning and their Application in Bioinformatics

@inproceedings{Ding2015DiversifiedEC,
  title={Diversified Ensemble Classifiers for Highly Imbalanced Data Learning and their Application in Bioinformatics},
  author={Zejin Jason Ding},
  year={2015}
}
In this dissertation, the problem of learning from highly imbalanced data is studied. Imbalance data learning is of great importance and challenge in many real applications. Dealing with a minority class normally needs new concepts, observations and solutions in order to fully understand the underlying complicated models. We try to systematically review and solve this special learning task in this dissertation. We propose a new ensemble learning framework—Diversified Ensemble Classifiers for… CONTINUE READING
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