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Proceedings Paper

Support vector machines for photometric redshift measurement of quasars
Author(s): Hongwen Zheng; Yanxia Zhang
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Paper Abstract

Based on photometric and spectroscopic data of quasars from SDSS DR7 and UKDISS DR7, support vector machines (SVM) is applied to predict photometric redshifts of quasars. Different input patterns are tried and the best pattern is presented. Comparing the results using optical data with that using optical and infrared data, the experimental results show that the accuracy improves with data from more bands. In addition, the quasar sample is firstly clustered into two groups by one-class SVM, then the photometric redshifts of the two groups are separately estimated by means of SVM. The results based on the whole sample and the combined results from the two groups are comparable.

Paper Details

Date Published: 24 September 2012
PDF: 8 pages
Proc. SPIE 8451, Software and Cyberinfrastructure for Astronomy II, 845133 (24 September 2012); doi: 10.1117/12.925761
Show Author Affiliations
Hongwen Zheng, North China Electric Power Univ. (China)
Yanxia Zhang, Key Lab. of Optical Astronomy, National Astronomical Observatories, Nanjing Institute of Astronomica (China)
National Astronomical Observatories, Nanjing Institute of Astronomal Optics & Technology (China)

Published in SPIE Proceedings Vol. 8451:
Software and Cyberinfrastructure for Astronomy II
Nicole M. Radziwill; Gianluca Chiozzi, Editor(s)

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