NDLI: Simple rule-based ensemble classifiers for cancer DNA microarray data classification

Content Provider	IEEE Xplore Digital Library
Author	Hualong Yu Sen Xu
Copyright Year	2011
Description	Author affiliation: School of Information Engineering, Yancheng Institute of Technology, China (Sen Xu) \|\| School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, China (Hualong Yu)
Abstract	DNA microarray, which is one of the most important molecular biology technologies in post-genomic era, has been widely applied in medical field, especially for cancer classification. However, it is difficult to acquire excellent classification accuracy by using traditional classification approaches due to microarray datasets are extremely asymmetric in dimensionality. In recent years, ensemble classifiers which may obtain better classification accuracy and robustness have attracted more interests in this field but it is more time-consuming. Therefore, this paper proposed a novel ensemble classification method named as SREC(Simple Rule-based Ensemble Classifiers). Firstly, the classification contribution of each gene is evaluated by a novel strategy and the corresponding classification rule is extracted. Then we rank all genes to select some important ones. At last, the rules of the selected genes are assembled by weighted-voting to make decision for testing samples. It has been demonstrated the proposed method may improve classification accuracy with lower time-complexity than traditional classification methods.
Starting Page	2555
Ending Page	2558
File Size	219155
Page Count	4
File Format	PDF
ISBN	9781424497621
e-ISBN	9781424497638
DOI	10.1109/CSSS.2011.5974135
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training DNA microarray Accuracy Feature selection Ensemble classifiers Feature extraction Colon Cancer Signal to noise ratio Testing
Content Type	Text
Resource Type	Article

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