Spectroscopy and Spectral Analysis, Volume. 38, Issue 7, 2307(2018)
Stellar Spectra Classification Method Based on Multi-Class Support Vector Machine
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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ZHANG Jing, LIU Zhong-bao, SONG Wen-ai, FU Li-zhen, ZHANG Yong-lai. Stellar Spectra Classification Method Based on Multi-Class Support Vector Machine[J]. Spectroscopy and Spectral Analysis, 2018, 38(7): 2307
Received: Jul. 30, 2017
Accepted: --
Published Online: Jul. 24, 2018
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