  We present a novel method capable of creating optimal eigenspectra from
multicolor redshift surveys for photometric redshift estimation. Our iterative
training algorithm modifies the templates to represent the photometric
measurements better. We present a short description of our algorithm here. We
show that the corrected templates give more precise photometric redshifts,
essentially a ``free'' feature, since we were not fitting for the redshifts
themselves.
