2015
DOI: 10.1134/s1063773715070038
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High-accuracy redshift measurements for galaxy clusters at z < 0.45 based on SDSS-III photometry

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Cited by 9 publications
(1 citation statement)
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“…Machine learning methods allow to measure photometric redshifts (photo-z ) of galaxy clusters from the accurate photometric redshift estimates for individual cluster galaxies. For example, the accuracy of σ ∼ 1% was obtained for clusters at redshifts z < 0.45 using SDSS data (Meshcheryakov et al, 2015). We have trained a galaxies photo-z model based on a quantile random forest described in Meshcheryakov et al (2018).…”
Section: Photometric Redshift Estimate Using Machine Learningmentioning
confidence: 99%
“…Machine learning methods allow to measure photometric redshifts (photo-z ) of galaxy clusters from the accurate photometric redshift estimates for individual cluster galaxies. For example, the accuracy of σ ∼ 1% was obtained for clusters at redshifts z < 0.45 using SDSS data (Meshcheryakov et al, 2015). We have trained a galaxies photo-z model based on a quantile random forest described in Meshcheryakov et al (2018).…”
Section: Photometric Redshift Estimate Using Machine Learningmentioning
confidence: 99%