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We present a new training set for estimating empirical photometric redshiftsof galaxies, which was created as part of the 2dFLenS project. This trainingset is located in a 700 sq deg area of the KiDS South field and is randomlyselected and nearly complete at r<19.5. We investigate the photometric redshiftperformance obtained with ugriz photometry from VST-ATLAS and W1/W2 from WISE,based on several empirical and template methods. The best redshift errors areobtained with kernel-density estimation, as are the lowest biases, which areconsistent with zero within statistical noise. The 68th percentiles of theredshift scatter for magnitude-limited samples at r<(15.5, 17.5, 19.5) are(0.014, 0.017, 0.028). In this magnitude range, there are no known ambiguitiesin the colour-redshift map, consistent with a small rate of redshift outliers.In the fainter regime, the KDE method produces p(z) estimates per galaxy thatrepresent unbiased and accurate redshift frequency expectations. The p(z) sumover any subsample is consistent with the true redshift frequency plus Poissonnoise. Further improvements in redshift precision at r<20 would mostly beexpected from filter sets with narrower passbands to increase the sensitivityof colours to small changes in redshift.

The 2-degree Field Lensing Survey: photometric redshifts from a large new training sample to r<19.5