Support Vector Machines for Photometric Redshift Estimation from Broadband Photometry

Support Vector Machines for Photometric Redshift Estimation from Broadband Photometry

Photometric redshifts have been regarded as efficient and effective measures for studying the statistical properties of galaxies and their evolution. In this paper, we introduce SVM_Light, a freely available software package using support vector machines (SVM) for photometric redshift estimation. Th...

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Bibliographic Details
Main Authors: Dan Wang, Yanxia Zhang, Yongheng Zhao
Format: Article
Language:English
Published: Ubiquity Press 2007-08-01
Series:Data Science Journal
Subjects:
Galaxies
Distances
Redshifts
Support vector machine
Online Access:http://datascience.codata.org/articles/447

Internet

http://datascience.codata.org/articles/447

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