Spectroscopy and Spectral Analysis, Volume. 33, Issue 2, 464(2013)
Data Mining for Cataclysmic Variables Candidates in SDSS-DR8
An automatic and efficient method for cataclysmic variables candidates is presented in this paper. The nonlinear locally linear embedding-LLE method is applied in the newly released SDSS-DR8 spectra. Spectra are dimension-reduced by LLE and classified by artificial neural network. The greatly reduced final candidates can be identified manually. 6 new CVs candidates were found in the experiment, and the compare between LLE with PCA shows the feasibility of nonlinear method in data mining in astronomical data.
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JIANG Bin, PAN Jing-chang, WANG Wei. Data Mining for Cataclysmic Variables Candidates in SDSS-DR8[J]. Spectroscopy and Spectral Analysis, 2013, 33(2): 464
Received: Jun. 25, 2012
Accepted: --
Published Online: Mar. 27, 2013
The Author Email: Bin JIANG (jiangbin@sdu.edu.cn)