Photometric redshift estimation using Gaussian processes

We present a comparison between Gaussian processes (GPs) and artificial neural networks (ANNs) as methods for determining photometric redshifts for galaxies, given training-set data. In particular, we compare their degradation in performance as the training-set size is degraded in ways which might b...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Monthly notices of the Royal Astronomical Society 2010-06, Vol.405 (2), p.987-994
Hauptverfasser:	Bonfield, D. G., Sun, Y., Davey, N., Jarvis, M. J., Abdalla, F. B., Banerji, M., Adams, R. G.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Astronomy Comparative studies Degradation Earth, ocean, space Errors Estimating techniques Exact sciences and technology galaxies: distances and redshifts Learning theory methods: data analysis Neural networks Regression Spectroscopy surveys Training
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!