title: [Data mining approach to cataclysmic variables candidates based on random forest algorithm].
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.
authors.affiliation: National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China. jiangbin@sdu.edu.cn
authors.forename: Bin
authors.initials: B
authors.lastname: Jiang
authors.forename: A-li
authors.initials: AL
authors.lastname: Luo
authors.forename: Yong-heng
authors.initials: YH
authors.lastname: Zhao