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MLZ: Machine Learning for photo-Z

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MLZ: Machine Learning for photo-Z

Postby mgckind » Wed Jan 15, 2014 7:38 pm

MLZ: Machine Learning for photo-Z

Abstract: The parallel Python framework MLZ (Machine Learning and photo-Z) computes fast and robust photometric redshift PDFs using Machine Learning algorithms. It uses a supervised technique with prediction trees and random forest through TPZ that can be used for a regression or a classification problem, or a unsupervised methods with self organizing maps and random atlas called SOMz. These machine learning implementations can be efficiently combined into a more powerful one resulting in robust and accurate probability distributions for photometric redshifts.

Credit: Carrasco Kind, Matias; Brunner, Robert


Bibcode: 2014ascl.soft03003C

ID: ascl:1403.003
Last edited by Ada Coda on Sat Jan 27, 2018 5:45 pm, edited 1 time in total.
Reason: Updated code entry.

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Re: MLZ: Machine Learning for photo-Z

Postby owlice » Fri Sep 26, 2014 4:51 am

Code-seeking owl at your service

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