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Estimating photometric redshifts using genetic algorithms

Miles, Nick and Freitas, Alex A. and Serjeant, Stephen (2006) Estimating photometric redshifts using genetic algorithms. In: Ellis, Richard and Allen, Tony and Tuson, Andrew, eds. Applications and Innovations in Intelligent Systems XIV Proceedings of AI-2006, the Twenty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. Springer, New York, USA, pp. 75-87. ISBN 1-84628-665-4. (doi:10.1007/978-1-84628-666-7_6) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:14385)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1007/978-1-84628-666-7_6

Abstract

Photometry is used as a cheap and easy way to estimate redshifts of galaxies, which would otherwise require considerable amounts of expensive telescope time. However, the analysis of photometric redshift datasets is a task where it is sometimes difficult to achieve a high classification accuracy. This work presents a custom Genetic Algorithm (GA) for mining the Hubble Deep Field North (HDF-N) datasets to achieve accurate IF-THEN classification rules. This kind of knowledge representation has the advantage of being intuitively comprehensible to the user, facilitating astronomers' interpretation of discovered knowledge. The GA is tested against the state of the art decision tree algorithm C5.0 [6] achieving significantly better results.

Item Type: Book section
DOI/Identification number: 10.1007/978-1-84628-666-7_6
Uncontrolled keywords: genetic algorithms, data mining, astronomy, classification rules
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:03 UTC
Last Modified: 16 Nov 2021 09:52 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/14385 (The current URI for this page, for reference purposes)

University of Kent Author Information

Freitas, Alex A..

Creator's ORCID: https://orcid.org/0000-0001-9825-4700
CReDIT Contributor Roles:

Serjeant, Stephen.

Creator's ORCID:
CReDIT Contributor Roles:
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