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Photometric redshift estimation based on data mining with PhotoRApToR

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.

preprint2015arXivOpen access
Stefano CavuotiMassimo BresciaVirgilio De StefanoGiuseppe Longo
astro-ph.IM
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Open access4 authors1 topic
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Stefano CavuotiMassimo BresciaVirgilio De StefanoGiuseppe Longo

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