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| Stellar Spectra Classification Method Based on Multi-Class Support Vector Machine |
| ZHANG Jing, LIU Zhong-bao*, SONG Wen-ai, FU Li-zhen, ZHANG Yong-lai |
| School of Software, North University of China, Taiyuan 030051, China |
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Abstract Support vector machine (SVM), a typical classification method, has been widely used in stellar spectra classification. It performs well in practice, while it encounters the multi-class classification challenge. In order to solve the problem above, multi-class support vector machine (MCSVM) was proposed in this paper based on the in-depth analysis of SVM. Meanwhile, the stellar spectra classification model based on multi-class support vector machine was constructed. The advantage of the proposed method is that the samples’ class can be determined by a classification process. Comparative experiments with the existed multi-class classification method on the SDSS DR8 datasets verify the effectiveness of the proposed method.
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Received: 2017-07-30
Accepted: 2017-11-16
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Corresponding Authors:
LIU Zhong-bao
E-mail: liz_zhongbao@hotmail.com
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