ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

MLZ: Machine Learning for photo-Z

Discussion topics for individual codes
mgckind
Posts: 2
Joined: Fri Apr 19, 2013 2:17 am

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

Site: https://github.com/mgckind/MLZ
http://adsabs.harvard.edu/abs/2014MNRAS.442.3380C

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.

User avatar
owlice
Guardian of the Codes
Posts: 1094
Joined: Wed Aug 04, 2004 4:18 pm
Location: Washington, DC

Re: MLZ: Machine Learning for photo-Z

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

Code-seeking owl at your service


Return to “Astrophysics Source Code Library”

Who is online

Users browsing this forum: No registered users and 5 guests

cron