Photometric identification of BHB stars J/A+A/522/A88 ivo://CDS.VizieR/J/A+A/522/A88 doi:10.26093/cds/vizier.35220088 CDS Smith K.W. Bailer-Jones C.A.L. Klement R.J. Xue X.X. 2011-02-11T05:00:35Z 2010-11-05T10:56:31Z CDS support team CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France cds-question@unistra.fr milky-way-galaxy horizontal-branch-stars visible-astronomy sloan-photometry We investigate the performance of some common machine learning techniques in identifying Blue Horizontal Branch (BHB) stars from photometric data. To train the machine learning algorithms, we use previously published spectroscopic identifications of BHB stars from Sloan Digital Sky Survey (SDSS) data. We investigate the performance of three different techniques, namely k nearest neighbour classification, kernel density estimation for discriminant analysis and a support vector machine (SVM). We discuss the performance of the methods in terms of both completeness (what fraction of input BHB stars are successfully returned as BHB stars) and contamination (what fraction of contaminating sources end up in the output BHB sample). We discuss the prospect of trading off these values, achieving lower contamination at the expense of lower completeness, by adjusting probability thresholds for the classification. We also discuss the role of prior probabilities in the classification performance, and we assess via simulations the reliability of the dataset used for training. Overall it seems that no-prior gives the best completeness, but adopting a prior lowers the contamination. We find that the support vector machine generally delivers the lowest contamination for a given level of completeness, and so is our method of choice. Finally, we classify a large sample of SDSS Data Release 7 (DR7) photometry using the SVM trained on the spectroscopic sample. We identify 27,074 probable BHB stars out of a sample of 294,652 stars. We derive photometric parallaxes and demonstrate that our results are reasonable by comparing to known distances for a selection of globular clusters. We attach our classifications, including probabilities, as an electronic table, so that they can be used either directly as a BHB star catalogue, or as priors to a spectroscopic or other classification method. We also provide our final models so that they can be directly applied to new data. 2010A&A...522A..88S https://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/522/A88 Catalog Research IsServedBy TAP VizieR generic service IsServedBy Conesearch service related-to II/294 : The SDSS Photometric Catalog, Release 7 (Adelman-McCarthy+, 2009) http://www.sdss.org : SDSS Home Page https://cds.unistra.fr/vizier-org/licences_vizier.html https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/522/A88 https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/522/A88 http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/522/A88 https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/522/A88 https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/522/A88 http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/522/A88 GET text/xml+votable https://tapvizier.cds.unistra.fr/TAPVizieR/tap Cone search capability for table J/A+A/522/A88/table7 (Catalogue of SDSS BHB candidates) https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/522/A88/table7? https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/522/A88/table7? http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/522/A88/table7? 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Should Not be used for identification. meta.record int y.alpha Product of weight and class label for each support vector stat.fit.param double u-g Standardized dereddened u-g colour phot.color;em.opt.U;em.opt.B double g-r Standardized dereddened g-r colour phot.color;em.opt.B;em.opt.R double r-i Standardized dereddened r-i colour phot.color;em.opt.R;em.opt.I double i-z Standardized dereddened i-z colour phot.color;em.opt.I;em.opt.I double
J/A+A/522/A88/tablea4 Model data for two-class SVM model recno Record number assigned by the VizieR team. Should Not be used for identification. meta.record int y.alpha Product of weight and class label for each support vector stat.fit.param double u-g Standardized dereddened u-g colour phot.color;em.opt.U;em.opt.B double g-r Standardized dereddened g-r colour phot.color;em.opt.B;em.opt.R double r-i Standardized dereddened r-i colour phot.color;em.opt.R;em.opt.I double i-z Standardized dereddened i-z colour phot.color;em.opt.I;em.opt.I double
J/A+A/522/A88/table7 Catalogue of SDSS BHB candidates recno Record number assigned by the VizieR team. Should Not be used for identification. meta.record int ObjID SDSS ObjID from PhotoObj table meta.id char plate ? SDSS plate from specObj table when available obs.field int nullable MJD ? SDSS MJD from specObj table when available time.epoch int nullable fiber ? SDSS fiber from specObj table when available meta.note int nullable umag SDSS u-band psf magnitude mag phot.mag;em.opt.U float e_umag SDSS u-band magnitude error mag stat.error;phot.mag;em.opt.U float gmag SDSS g-band psf magnitude mag phot.mag;em.opt.B float e_gmag SDSS g-band magnitude error mag stat.error;phot.mag;em.opt.B float rmag SDSS r-band psf magnitude mag phot.mag;em.opt.R float e_rmag SDSS r-band magnitude error mag stat.error;phot.mag;em.opt.R float imag SDSS i-band psf magnitude mag phot.mag;em.opt.I float e_imag SDSS i-band magnitude error mag stat.error;phot.mag;em.opt.I float zmag SDSS z-band psf magnitude mag phot.mag;em.opt.I float e_zmag SDSS z-band magnitude error mag stat.error;phot.mag;em.opt.I float uext u-band extinction from SDSS pipeline (2) mag phys.absorption float gext g-band extinction from SDSS pipeline (2) mag phys.absorption float rext r-band extinction from SDSS pipeline (2) mag phys.absorption float iext i-band extinction from SDSS pipeline (2) mag phys.absorption float zext z-band extinction from SDSS pipeline (2) mag phys.absorption float Type Object category, from Xue et al., 2008ApJ...684.1143X (3) src.class char Psvm Probability of BHB from SVM (support vector machine) model (4) stat.fit.goodness float e_Psvm Standard deviation of Psvm for 10 trials (4) stat.stdev float Prior 2d prior applied to probability. stat.fit.param float modP Psvm probability modified by prior (5) stat.fit.goodness double Dist Estimated distance in kpc (6) kpc pos.distance;pos.heliocentric float e_Dist Fractional (relative) error on the distance stat.error double SDSS Display the SDSS data for this quasar meta.ref.url char DR7 Details from the SDSS-DR7 Photometric Catalog (Cat. II/294) meta.ref.url char RAJ2000 Right ascension in decimal degrees (J2000.0) (1) deg pos.eq.ra;meta.main indexed DEJ2000 Declination in decimal degrees (J2000.0) (1) deg pos.eq.dec;meta.main indexed