NDLI: Incremental wrapper based gene selection with Markov blanket

Content Provider	IEEE Xplore Digital Library
Author	Wang, Aiguo An, Ning Chen, Guilin Yang, Jing Li, Lian Alterovitz, Gil
Copyright Year	2014
Description	Author affiliation: School of Computer and Information, Hefei University of Technology, Hefei, China (Wang, Aiguo; An, Ning; Yang, Jing; Li, Lian) \|\| School of Computer and Information Engineering, Chuzhou University, Chuzhou, China (Chen, Guilin) \|\| Center for Biomedical Informatics, Harvard Medical School, Cambridge, USA (Alterovitz, Gil)
Abstract	Gene selection plays a crucial role in the analysis of microarray data with high dimensionality and small sample size. Incremental wrapper based feature subset selection (FSS) methods, among various feature selection approaches, tend to obtain high quality feature subset and better classification accuracy than filter methods, while it is much more time consuming since the interdependence and redundancy between features is evaluated in a wrapper way. In this paper, we explore to introduce Markov Blanket (MB) into incremental wrapper based FSS process. Rather than evaluate the quality of all the features ranked by a filter method, our proposal eliminates features that are redundant to the newly selected one via MB during the wrapper evaluation process to reduce the number of wrappers, enabling us to select the relevant features and eliminate redundant ones efficiently. To verify the effectiveness and efficiency of the proposed approach, experimental comparisons on six publicly available microarray data are conducted with two typical classifiers with different metrics, Naïve Bayes and 1-Nearest-Neighbor. Experimental results demonstrate that our approach greatly speeds up the feature selection process, obtains more compact feature subset and achieves better classification accuracy compared to that without MB for both two-category and multi-category problems.
Starting Page	74
Ending Page	79
File Size	294516
Page Count	6
File Format	PDF
ISBN	9781479956692
DOI	10.1109/BIBM.2014.6999251
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-02
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Markov Blanket Accuracy Uncertainty gene selection microarray data Markov processes Filtering algorithms wrapper Classification algorithms Tumors symmetric uncertainty
Content Type	Text
Resource Type	Article

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