Heterogeneous ensemble approach with discriminative features and modified-SMOTEbagging for pre-miRNA classification

@inproceedings{Lertampaiporn2013HeterogeneousEA,
  title={Heterogeneous ensemble approach with discriminative features and
modified-SMOTEbagging for pre-miRNA classification},
  author={Supatcha Lertampaiporn and Chinae Thammarongtham and Chakarida Nukoolkit and Boonserm Kaewkamnerdpong and Marasri Ruengjitchatchawalya},
  booktitle={Nucleic acids research},
  year={2013}
}
An ensemble classifier approach for microRNA precursor (pre-miRNA) classification was proposed based upon combining a set of heterogeneous algorithms including support vector machine (SVM), k-nearest neighbors (kNN) and random forest (RF), then aggregating their prediction through a voting system. Additionally, the proposed algorithm, the classification performance was also improved using discriminative features, self-containment and its derivatives, which have shown unique structural… CONTINUE READING

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