[1]CAO Jin,ZHANG Li,LI Fanzhang.A noval support vector data description-based feature selection method[J].CAAI Transactions on Intelligent Systems,2015,10(2):215-220.[doi:10.3969/j.issn.1673-4785.201405063]
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A noval support vector data description-based feature selection method
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
10
Number of periods:
2015 2
Page number:
215-220
Column:
学术论文—人工智能基础
Public date:
2015-04-25
- Title:
- A noval support vector data description-based feature selection method
- Keywords:
- support vector data description; feature selection; recursive computation; recursive feature elimination; cancer recognition; gene expression
- CLC:
- TP391
- DOI:
- 10.3969/j.issn.1673-4785.201405063
- Abstract:
- There have been proposed feature selection methods based on support vector data description (SVDD), or SVDD-radius-RFE and SVDD-dual-objective-RFE. These methods are time consuming due to the high computational complexity. To remedy it, a support vector data description-based feature selection method is proposed, ie SVDD-RFE. In this method, feature elimination depends on the energy of directions in the center of hypersphere. In addition, a scheme of recursive feature elimination (RFE) is introduced to iteratively remove irrelevant features. Experimental results on the Leukemia dataset showed that this method has fast speed for feature selection, and the selected features are efficient for subsequent classification tasks.
- References:
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Last Update:
2015-06-15