Robust classification ensemble method for microarray data

Dongjun Chung, Hyunjoong Kim

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


The objective of this study is to develop an accurate and robust classification ensemble method suitable for microarray data with noises. We proposed an algorithm, pattern match (PM)-bagging, which performs well in accuracy and is robust to noise variables and noise observations. From the experiments with real data set, the performance of the proposed method is found quite comparable and not much degraded even when the data set has noise variables or noise observations, while some other ensemble methods showed degradations of performance. A bias and variance decomposition showed that the success of the proposed method is due to an effective reduction of both bias and variance.

Original languageEnglish
Pages (from-to)504-518
Number of pages15
JournalInternational Journal of Data Mining and Bioinformatics
Issue number5
Publication statusPublished - 2011 Oct

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Biochemistry, Genetics and Molecular Biology(all)
  • Library and Information Sciences


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