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We present the methodology and data behind the photometric redshift databaseof the Sloan Digital Sky Survey Data Release 12 (SDSS DR12). We adopt a hybridtechnique, empirically estimating the redshift via local regression on aspectroscopic training set, then fitting a spectrum template to obtainK-corrections and absolute magnitudes. The SDSS spectroscopic catalog wasaugmented with data from other, publicly available spectroscopic surveys tomitigate target selection effects. The training set is comprised of $1,976,978$galaxies, and extends up to redshift $z\approx 0.8$, with a useful coverage ofup to $z\approx 0.6$. We provide photometric redshifts and realistic errorestimates for the $208,474,076$ galaxies of the SDSS primary photometriccatalog. We achieve an average bias of $\overline{\Delta z_{\mathrm{norm}}} =5.84 \times 10^{-5}$, a standard deviation of $\sigma \left(\Deltaz_{\mathrm{norm}}\right)=0.0205$, and a $3\sigma$ outlier rate of $P_o=4.11\%$when cross-validating on our training set. The published redshift errorestimates and photometric error classes enable the selection of galaxies withhigh quality photometric redshifts. We also provide a supplementary error mapthat allows additional, sophisticated filtering of the data.

Photometric redshifts for the SDSS Data Release 12