Photometric redshift estimation based on data mining with PhotoRApToR

Journal
Date Issued
2015
Author(s)
•
•
De Stefano, V.
•
Longo, G.
DOI
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 multi-layer neural network trained by the Quasi Newton learning rule, and special tools dedicated to pre- and post-processing data. PhotoRApToR has been successfully tested on several scientific cases. The application is available for free download from the DAME Program web site.

Volume
39
Issue
1
Start page
45
Uri
Url
Issn Identifier
0922-6435
Ads BibCode
2015ExA....39...45C
Rights
open.access
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