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3 results

  • Photometric Redshift Techniques in Big-data Era

  • Yan-Xia Zhang, Yong-Heng Zhao
  • Journal:
    Proceedings of the International Astronomical Union / Volume 11 / Issue S319 / August 2015
    Published online by Cambridge University Press:
    17 August 2016, p. 57
    Print publication:
    August 2015
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  • Photometric data increase with large survey projects running. The huge volume of data influences the means and methods to deal with them. As such, the techniques of photometric redshift estimation based on photometric data must be developed and improved.

  • Comparison of Approaches to Photometric Redshift Estimation of Quasars

  • Yang Tu, Yan-Xia Zhang, Yong-Heng Zhao, Hai-Jun Tian
  • Journal:
    Proceedings of the International Astronomical Union / Volume 11 / Issue S319 / August 2015
    Published online by Cambridge University Press:
    17 August 2016, p. 146
    Print publication:
    August 2015
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  • We probe many kinds of approaches used for photometric redshift estimation of quasars, including KNN (K-nearest neighbor algorithm), Lasso (Least Absolute Shrinkage and Selection Operator), PLS (Partial Least Square regression), ridge regression, SGD (Stochastic Gradient Descent) and Extra-Trees.

  • Improving Accuracy of Quasars' Photometric Redshift Estimation by Integration of KNN and SVM

  • Bo Han, Hongpeng Ding, Yanxia Zhang, Yongheng Zhao
  • Journal:
    Proceedings of the International Astronomical Union / Volume 11 / Issue A29A / August 2015
    Published online by Cambridge University Press:
    27 October 2016, p. 209
    Print publication:
    August 2015
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  • Catastrophic failure is an unsolved problem existing in the most photometric redshift estimation approaches for a long history. In this study, we propose a novel approach by integration of k-nearest-neighbor (KNN) and support vector machine (SVM) methods together. Experiments based on the quasar sample from SDSS show that the fusion approach can significantly mitigate catastrophic failure and improve the accuracy of photometric redshift estimation.