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<ri:Resource created="2023-02-28T07:51:36Z" status="active" updated="2025-05-19T09:50:00Z" version="1.2" xmlns:cs="http://www.ivoa.net/xml/ConeSearch/v1.0" xmlns:ri="http://www.ivoa.net/xml/RegistryInterface/v1.0" xmlns:vr="http://www.ivoa.net/xml/VOResource/v1.0" xmlns:vs="http://www.ivoa.net/xml/VODataService/v1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.ivoa.net/xml/ConeSearch/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/ConeSearch.xsd http://www.ivoa.net/xml/VOResource/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/VOResource.xsd http://www.ivoa.net/xml/VODataService/v1.1 http://vo.ari.uni-heidelberg.de/docs/schemata/VODataService.xsd" xsi:type="vs:CatalogService"><title>Machine learning predicted AGNs in HSC-Wide region</title><shortName>J/ApJ/920/68</shortName><identifier>ivo://CDS.VizieR/J/ApJ/920/68</identifier><altIdentifier>doi:10.26093/cds/vizier.19200068</altIdentifier><curation><publisher ivo-id="ivo://CDS">CDS</publisher><creator><name>Chang Y.-Y.</name></creator><creator><name>Hsieh B.-C.</name></creator><creator><name>Wang W.-H.</name></creator><creator><name>Lin Y.-T.</name></creator><creator><name>Lim C.-F.</name></creator><creator><name>Toba Y.,Zhong Y.,Chang S.-Y.</name></creator><date role="Updated">2023-09-27T10:27:01Z</date><date role="Created">2023-02-28T07:51:36Z</date><contact><name>CDS support team</name><address>CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France</address><email>cds-question@unistra.fr</email></contact></curation><content><subject>active-galactic-nuclei</subject><subject>infrared-photometry</subject><subject>visible-astronomy</subject><subject>photometry</subject><description>We investigate the performance of machine-learning techniques in classifying active galactic nuclei (AGNs), including X-ray-selected AGNs (XAGNs), infrared-selected AGNs (IRAGNs), and radio-selected AGNs (RAGNs). Using the known physical parameters in the Cosmic Evolution Survey (COSMOS) field, we are able to create quality training samples in the region of the Hyper Suprime-Cam (HSC) survey. We compare several Python packages (e.g., scikit- learn, Keras, and XGBoost) and use XGBoost to identify AGNs and show the performance (e.g., accuracy, precision, recall, F1 score, and AUROC). Our results indicate that the performance is high for bright XAGN and IRAGN host galaxies. The combination of the HSC (optical) information with the Wide-field Infrared Survey Explorer band 1 and band 2 (near-infrared) information performs well to identify AGN hosts. For both type 1 (broad-line) XAGNs and type 1 (unobscured) IRAGNs, the performance is very good by using optical-to-infrared information. These results can apply to the five-band data from the wide regions of the HSC survey and future all-sky surveys.</description><source format="bibcode">2021ApJ...920...68C</source><referenceURL>https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/920/68</referenceURL><type>Catalog</type><contentLevel>Research</contentLevel><relationship><relationshipType>IsServedBy</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/TAP">TAP VizieR generic service</relatedResource></relationship><relationship><relationshipType>IsServedBy</relationshipType><relatedResource>Conesearch service</relatedResource></relationship><relationship><relationshipType>related-to</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/640/167">J/ApJ/640/167 : AGNs and ULIRGs in the CDF-South (Alonso-Herrero+, 2006)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/451/457">J/A+A/451/457 : X-ray properties of AGN in CDFS (Tozzi+, 2006)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/391/369">J/MNRAS/391/369 : New z&gt;=3.6 QSOs from FIRST-SDSS DR5 (Carballo+, 2008)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/690/1236">J/ApJ/690/1236 : COSMOS photometric redshift catalog (Ilbert+, 2009)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/728/58">J/ApJ/728/58 : Swift-BAT survey of AGNs (Burlon+, 2011)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/AJ/141/189">J/AJ/141/189 : Classifiers for star/galaxy separation (Vasconcellos+, 2011)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/421/1569">J/MNRAS/421/1569 : Properties of 18286 SDSS radio galaxies (Best+, 2012)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/437/968">J/MNRAS/437/968 : AGN automatic photometric classification (Cavuoti+, 2014)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/782/41">J/ApJ/782/41 : 231 AGN candidates from the 2FGL catalog (Doert+, 2014)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/219/8">J/ApJS/219/8 : SFR for WISE + SDSS spectroscopic galaxies (Chang+, 2015)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/806/110">J/ApJ/806/110 : ALESS survey; SMGs in the ECDF-S data (da Cunha+, 2015)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/819/62">J/ApJ/819/62 : The COSMOS-Legacy Survey (CLS) catalog (Civano+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/224/24">J/ApJS/224/24 : The COSMOS2015 catalog (Laigle+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/817/34">J/ApJ/817/34 : C-COSMOS Legacy multiwavelength catalog (Marchesi+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/457/110">J/MNRAS/457/110 : Northern XMM-XXL field AGN catalog (Menzel+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/820/8">J/ApJ/820/8 : 3FGL sources stat. classifications (Saz Parkinson+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/476/3661">J/MNRAS/476/3661 : Morphology of SDSS galaxies (Dominguez+, 2018)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/619/A14">J/A+A/619/A14 : Classification-aided zph estimation (Fotopoulou+, 2018)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/611/A97">J/A+A/611/A97 : Photo. quasar candidates in Stripe 82 (Pasquet-Itam+, 2018)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/243/15">J/ApJS/243/15 : WERGS. 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