Support Vector Machines for Quasar Selection
Identifieur interne : 000A59 ( Main/Exploration ); précédent : 000A58; suivant : 000A60Support Vector Machines for Quasar Selection
Auteurs : NANBO PENG [République populaire de Chine] ; YANXIA ZHANG [République populaire de Chine] ; YONGHENG ZHAO [République populaire de Chine]Source :
- Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2010.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
We introduce an automated method called Support Vector Machines (SVMs) for quasar selection in order to compile an input catalogue for the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and improve the efficiency of its 4000 fibers. The data are adopted from the Sloan Digital Sky Survey (SDSS) Data Release Seven (DR7) which is the latest world release now. We carefully study the discrimination of quasars from stars by finding the hyperplane in high-dimensional space of colors with different combinations of model parameters in SVMs and give a clear way to find the optimal combination (C-+ = 2, C+- = 2, kernel = RBF, gamma = 3.2). Furthermore, we investigate the performances of SVMs for the sake of predicting the photometric redshifts of quasar candidates and get optimal model parameters of (w = 0.001, C-+ = 1, C+- = 2, kernel = RBF, gamma = 7.5) for SVMs. Finally, the experimental results show that the precision and the recall of SVMs for separating quasars from stars both can be over 95%. Using the optimal model parameters, we estimate the photometric redshifts of 39353 identified quasars, and find that 72.99% of them are consistent with the spectroscopic redshifts within |Δz| < 0.2. This approach is effective and applicable for our problem.
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 000116
- to stream PascalFrancis, to step Curation: 000129
- to stream PascalFrancis, to step Checkpoint: 000065
- to stream Main, to step Merge: 000A64
- to stream Main, to step Curation: 000A59
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Support Vector Machines for Quasar Selection</title><author><name sortKey="Nanbo Peng" sort="Nanbo Peng" uniqKey="Nanbo Peng" last="Nanbo Peng">NANBO PENG</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Key Laboratory of Optical Astronomy, National Astronomical Observatories; Chinese Academy of Sciences</s1><s2>100012 Beijing</s2><s3>CHN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>République populaire de Chine</country><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yanxia Zhang" sort="Yanxia Zhang" uniqKey="Yanxia Zhang" last="Yanxia Zhang">YANXIA ZHANG</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Key Laboratory of Optical Astronomy, National Astronomical Observatories; Chinese Academy of Sciences</s1><s2>100012 Beijing</s2><s3>CHN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>République populaire de Chine</country><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yongheng Zhao" sort="Yongheng Zhao" uniqKey="Yongheng Zhao" last="Yongheng Zhao">YONGHENG ZHAO</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Key Laboratory of Optical Astronomy, National Astronomical Observatories; Chinese Academy of Sciences</s1><s2>100012 Beijing</s2><s3>CHN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>République populaire de Chine</country><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">11-0004555</idno><date when="2010">2010</date><idno type="stanalyst">PASCAL 11-0004555 INIST</idno><idno type="RBID">Pascal:11-0004555</idno><idno type="wicri:Area/PascalFrancis/Corpus">000116</idno><idno type="wicri:Area/PascalFrancis/Curation">000129</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">000065</idno><idno type="wicri:doubleKey">0277-786X:2010:Nanbo Peng:support:vector:machines</idno><idno type="wicri:Area/Main/Merge">000A64</idno><idno type="wicri:Area/Main/Curation">000A59</idno><idno type="wicri:Area/Main/Exploration">000A59</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Support Vector Machines for Quasar Selection</title><author><name sortKey="Nanbo Peng" sort="Nanbo Peng" uniqKey="Nanbo Peng" last="Nanbo Peng">NANBO PENG</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Key Laboratory of Optical Astronomy, National Astronomical Observatories; Chinese Academy of Sciences</s1><s2>100012 Beijing</s2><s3>CHN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>République populaire de Chine</country><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yanxia Zhang" sort="Yanxia Zhang" uniqKey="Yanxia Zhang" last="Yanxia Zhang">YANXIA ZHANG</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Key Laboratory of Optical Astronomy, National Astronomical Observatories; Chinese Academy of Sciences</s1><s2>100012 Beijing</s2><s3>CHN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>République populaire de Chine</country><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yongheng Zhao" sort="Yongheng Zhao" uniqKey="Yongheng Zhao" last="Yongheng Zhao">YONGHENG ZHAO</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Key Laboratory of Optical Astronomy, National Astronomical Observatories; Chinese Academy of Sciences</s1><s2>100012 Beijing</s2><s3>CHN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>République populaire de Chine</country><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author></analytic><series><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><title level="j" type="abbreviated">Proc. SPIE Int. Soc. Opt. Eng.</title><idno type="ISSN">0277-786X</idno><imprint><date when="2010">2010</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><title level="j" type="abbreviated">Proc. SPIE Int. Soc. Opt. Eng.</title><idno type="ISSN">0277-786X</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Color image</term><term>Color space</term><term>Discrimination</term><term>Hyperplane</term><term>Modeling</term><term>Multidimensional analysis</term><term>Photometry</term><term>Radial basis function</term><term>Sky</term><term>Statistical analysis</term><term>Telescope</term><term>Vector support machine</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Image couleur</term><term>Ciel</term><term>Télescope</term><term>Discrimination</term><term>Analyse n dimensionnelle</term><term>Espace chromatique</term><term>Analyse statistique</term><term>Classification à vaste marge</term><term>Hyperplan</term><term>Modélisation</term><term>Fonction base radiale</term><term>Photométrie</term><term>.</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We introduce an automated method called Support Vector Machines (SVMs) for quasar selection in order to compile an input catalogue for the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and improve the efficiency of its 4000 fibers. The data are adopted from the Sloan Digital Sky Survey (SDSS) Data Release Seven (DR7) which is the latest world release now. We carefully study the discrimination of quasars from stars by finding the hyperplane in high-dimensional space of colors with different combinations of model parameters in SVMs and give a clear way to find the optimal combination (C<sub>-+</sub> = 2, C<sub>+-</sub> = 2, kernel = RBF, gamma = 3.2). Furthermore, we investigate the performances of SVMs for the sake of predicting the photometric redshifts of quasar candidates and get optimal model parameters of (w = 0.001, C<sub>-+</sub> = 1, C<sub>+-</sub> = 2, kernel = RBF, gamma = 7.5) for SVMs. Finally, the experimental results show that the precision and the recall of SVMs for separating quasars from stars both can be over 95%. Using the optimal model parameters, we estimate the photometric redshifts of 39353 identified quasars, and find that 72.99% of them are consistent with the spectroscopic redshifts within |Δz| < 0.2. This approach is effective and applicable for our problem.</div></front></TEI><affiliations><list><country><li>République populaire de Chine</li></country><settlement><li>Pékin</li></settlement></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Nanbo Peng" sort="Nanbo Peng" uniqKey="Nanbo Peng" last="Nanbo Peng">NANBO PENG</name></noRegion><name sortKey="Yanxia Zhang" sort="Yanxia Zhang" uniqKey="Yanxia Zhang" last="Yanxia Zhang">YANXIA ZHANG</name><name sortKey="Yongheng Zhao" sort="Yongheng Zhao" uniqKey="Yongheng Zhao" last="Yongheng Zhao">YONGHENG ZHAO</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/CyberinfraV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000A59 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000A59 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= CyberinfraV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= Pascal:11-0004555
|texte= Support Vector Machines for Quasar Selection
}}
| This area was generated with Dilib version V0.6.25. |  |