Photometric Redshift Estimation on SDSS Data Using Random Forests

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dc.creatorCarliles, Samuel
dc.creatorBudavári, Tamás
dc.creatorHeinis, Sebastien
dc.creatorPriebe, Carey
dc.creatorSzalay, Alexander
dc.date2007-11-15
dc.date.accessioned2026-07-07T08:43:09Z
dc.date.available2026-07-07T08:43:09Z
dc.descriptionGiven multiband photometric data from the SDSS DR6, we estimate galaxy redshifts. We employ a Random Forest trained on color features and spectroscopic redshifts from 80,000 randomly chosen primary galaxies yielding a mapping from color to redshift such that the difference between the estimate and the spectroscopic redshift is small. Our methodology results in tight RMS scatter in the estimates limited by photometric errors. Additionally, this approach yields an error distribution that is nearly Gaussian with parameter estimates giving reliable confidence intervals unique to each galaxy photometric redshift.
dc.description4 pages, 4 figures, to be published in Proceedings of ADASS XVII
dc.identifierhttps://arxiv.org/abs/0711.2477
dc.identifierhttp://arxiv.org/abs/0711.2477
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/142216
dc.subjectAstrophysics
dc.titlePhotometric Redshift Estimation on SDSS Data Using Random Forests
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