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arXiv · 1501.06506

Photometric redshift estimation based on data mining with PhotoRApToR

Stefano Cavuoti·Massimo Brescia·Virgilio De Stefano·Giuseppe Longo
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Abstract

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.

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Stefano Cavuoti, Massimo Brescia, Virgilio De Stefano, Giuseppe Longo. 2015-01-26. Photometric redshift estimation based on data mining with PhotoRApToR. https://doi.org/10.1007/s10686-015-9443-4

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