Recognition of Multiple Imbalanced Cancer Types Based on DNA Microarray Data Using Ensemble Classifiers
Joint Authors
Yu, Hualong
Hong, Shufang
Yang, Xibei
Ni, Jun
Dan, Yuanyuan
Qin, Bin
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-08-26
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
DNA microarray technology can measure the activities of tens of thousands of genes simultaneously, which provides an efficient way to diagnose cancer at the molecular level.
Although this strategy has attracted significant research attention, most studies neglect an important problem, namely, that most DNA microarray datasets are skewed, which causes traditional learning algorithms to produce inaccurate results.
Some studies have considered this problem, yet they merely focus on binary-class problem.
In this paper, we dealt with multiclass imbalanced classification problem, as encountered in cancer DNA microarray, by using ensemble learning.
We utilized one-against-all coding strategy to transform multiclass to multiple binary classes, each of them carrying out feature subspace, which is an evolving version of random subspace that generates multiple diverse training subsets.
Next, we introduced one of two different correction technologies, namely, decision threshold adjustment or random undersampling, into each training subset to alleviate the damage of class imbalance.
Specifically, support vector machine was used as base classifier, and a novel voting rule called counter voting was presented for making a final decision.
Experimental results on eight skewed multiclass cancer microarray datasets indicate that unlike many traditional classification approaches, our methods are insensitive to class imbalance.
American Psychological Association (APA)
Yu, Hualong& Hong, Shufang& Yang, Xibei& Ni, Jun& Dan, Yuanyuan& Qin, Bin. 2013. Recognition of Multiple Imbalanced Cancer Types Based on DNA Microarray Data Using Ensemble Classifiers. BioMed Research International،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1003767
Modern Language Association (MLA)
Yu, Hualong…[et al.]. Recognition of Multiple Imbalanced Cancer Types Based on DNA Microarray Data Using Ensemble Classifiers. BioMed Research International No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-1003767
American Medical Association (AMA)
Yu, Hualong& Hong, Shufang& Yang, Xibei& Ni, Jun& Dan, Yuanyuan& Qin, Bin. Recognition of Multiple Imbalanced Cancer Types Based on DNA Microarray Data Using Ensemble Classifiers. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1003767
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1003767