| 光谱学与光谱分析 |
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| Data Mining Approach to Cataclysmic Variables Candidates Based on Random Forest Algorithm |
| JIANG Bin1,2,3, LUO A-li1, ZHAO Yong-heng1 |
1. National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
2. School of Mechanical, Electrical&Information Engineering, Shandong University at Weihai, Weihai 264209, China
3. Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract An automatic and efficient method for cataclysmic variables candidates is presented in the present paper. The identified CVs were selected as templates. A model was constructed by random forest algorithm with templates and random selected spectra. Wavelength ranking was described by the model and the classifier was constructed afterwards. Most of the non-candidates were excluded by the method. Template matching strategy was used to identify the final candidates which were analyzed to complement the templates as feedback. 16 new CVs candidates were found in the experiment that shows that our approach to finding special celestial bodies can be feasible in LAMOST.
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Received: 2011-03-10
Accepted: 2011-06-20
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Corresponding Authors:
JIANG Bin
E-mail: jiangbin@sdu.edu.cn
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