  Photometric redshifts (photo-z) are crucial to the scientific exploitation of
modern panchromatic digital surveys. In this paper we present PhotoRApToR
(Photometric Research Application To Redshift): a Java/C++ based desktop
application capable to solve non-linear regression and multi-variate
classification problems, in particular specialized for photo-z estimation. It
embeds a machine learning algorithm, namely a multilayer neural network trained
by the Quasi Newton learning rule, and special tools dedicated to pre- and
postprocessing data. PhotoRApToR has been successfully tested on several
scientific cases. The application is available for free download from the DAME
Program web site.
