Computer Science – Databases
Scientific paper
Dec 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008aipc.1082...76r&link_type=abstract
CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS: Proceedings of the International Conference: ``Classification and Di
Computer Science
Databases
1
Luminosities, Magnitudes, Effective Temperatures, Colors, And Spectral Classification, Magnetohydrodynamics And Plasmas, Galactic Center, Bar, Circumnuclear Matter, And Bulge, Astronomical Catalogs, Atlases, Sky Surveys, Databases, Retrieval Systems, Archives, Etc.
Scientific paper
We present several strategies that are being developed in order to classify and parameterize individual stars observed by Galactic surveys, and illustrate some results obtained from spectra obtained by the RAdial Velocity Experiment (RAVE) and the Sloan Digital Sky Survey (SDSS/SEGUE). We demonstrate the efficiency of our models for discrete source classification and stellar atmospheric parameter estimation (effective temperature, surface gravity, and metallicity), which use supervised machine learning algorithms along with a principal component analysis front-end compression phase that also enables knowledge discovery.
Bailer-Jones Coryn A. L.
Beers Timothy C.
Re Fiorentin Paola
Zwitter Tomaz
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