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Automated Classification of Quasars and Stars

Published online by Cambridge University Press:  03 June 2010

Yanxia Zhang
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China Email: [email protected]
Yongheng Zhao
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China Email: [email protected]
Hongwen Zheng
Affiliation:
North China Electronic Power University, Beijing, 102206, China Email: [email protected]
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We investigate selection and weighting of features by applying a random forest algorithm to multiwavelength data. Then we employ a k-nearest neighbor method to distinguish quasars from stars. We then compare the performance of this approach based on all features, weighted features, and selected features. We find that the k-nearest neighbor approach combined with random forests effectively separates quasars from stars.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2010