imDC: an ensemble learning method for imbalanced classification with miRNA data.

Journal: Genetics and molecular research : GMR
Published Date:

Abstract

Imbalances typically exist in bioinformatics and are also common in other areas. A drawback of traditional machine learning methods is the relatively little attention given to small sample classification. Thus, we developed imDC, which uses an ensemble learning concept in combination with weights and sample misclassification information to effectively classify imbalanced data. Our method showed better results when compared to other algorithms with UCI machine learning datasets and microRNA data.

Authors

  • C Y Wang
    School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China chunyu@hit.edu.cn.
  • L L Hu
    School of Information Science and Technology, Xiamen University, Xiamen, China.
  • M Z Guo
    School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
  • X Y Liu
    Guangzhou Accurate and Correct Test Company, Guangzhou 510663, China.
  • Q Zou
    School of Information Science and Technology, Xiamen University, Xiamen, China.