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Table · dataset · 2022

J-PLUS. STAR-GALAXY-QSO Classification

Listed in IVOA Registry (Virtual Observatory)

In modern astronomy, machine learning has proved to be efficient and effective in mining big data from the newest telescopes.

Description

In this study, we construct a supervised machine-learning algorithm to classify the objects in the Javalambre Photometric Local Universe Survey first data release (J-PLUS DR1). The sample set is featured with 12-waveband photometry and labeled with spectrum-based catalogs, including Sloan Digital Sky Survey (SDSS) spectroscopic data, the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), and VERON- CAT - the Veron Catalog of Quasars & AGN (VV13.

Cat. VII/258). The performance of the classifier is presented with the applications of blind test validations based on RAdial Velocity Extension (RAVE), the Kepler Input Catalog (KIC), the 2 MASS (the Two Micron All Sky Survey) Redshift Survey (2MRS), and the UV-bright Quasar Survey (UVQS).

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A new algorithm was applied to constrain the potential extrapolation that could decrease the performance of the machine-learning classifier. The accuracies of the classifier are 96.5% in the blind test and 97.0% in training cross-validation. The F1-scores for each class are presented to show the balance between the precision and the recall of the classifier.

We also discuss different methods to constrain the potential extrapolation.

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Provenance · 1 source records, 7 field assertions
SourceKeyLast seenRaw
IVOA Registry (Virtual Observatory)ivo://cds.vizier/j/a+a/659/a14411 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:astronomymapping · IVOA Registryconnector:ivoa_registry@1.0.0
descriptionsource · IVOA Registryconnector:ivoa_registry@1.0.0rr.resource.res_description
license_textsource · IVOA Registryconnector:ivoa_registry@1.0.0
publication_datesource · IVOA Registryconnector:ivoa_registry@1.0.0
titlesource · IVOA Registryconnector:ivoa_registry@1.0.0rr.resource.res_title
updated_datesource · IVOA Registryconnector:ivoa_registry@1.0.0