Automated novelty detection in the WISE survey with one-class support vector machines

Abstract

Wide-angle photometric surveys of previously uncharted sky areas or wavelength regimes will always bring in unexpected sources whose existence and properties cannot be easily predicted from earlier observations: novelties or even anomalies. Such objects can be efficiently sought for with novelty detection algorithms. Here we present an application of such a method, called one-class support vector machines (OCSVM), to search for anomalous patterns among sources preselected from the mid-infrared AllWISE catalogue covering the whole sky. To create a model of expected data we train the algorithm on a set of objects with spectroscopic identifications from the SDSS DR13 database, present also in AllWISE. OCSVM detects as anomalous those sources whose patterns - WISE photometric measurements in this case - are inconsistent with the model. Among the detected anomalies we find artefacts, such as objects with spurious photometry due to blending, but most importantly also real sources of genuine astrophysical interest. Among the latter, OCSVM has identified a sample of heavily reddened AGN/quasar candidates distributed uniformly over the sky and in a large part absent from other WISE-based AGN catalogues. It also allowed us to find a specific group of sources of mixed types, mostly stars and compact galaxies. By combining the semi-supervised OCSVM algorithm with standard classification methods it will be possible to improve the latter by accounting for sources which are not present in the training sample but are otherwise well-represented in the target set. Anomaly detection adds flexibility to automated source separation procedures and helps verify the reliability and representativeness of the training samples. It should be thus considered as an essential step in supervised classification schemes to ensure completeness and purity of produced catalogues.

14 pages, 15 figures

References in corpus (41)

• The Sloan Digital Sky Survey: Technical Summary
• The Wide-field Infrared Survey Explorer (WISE): Mission Description and Initial On-orbit Performance
• K-corrections and filter transformations in the ultraviolet, optical, and near infrared
• GLIMPSE: I. A SIRTF Legacy Project to Map the Inner Galaxy
• 2MASS Extended Source Catalog: Overview and Algorithms
• Mid-Infrared Selection of AGN with the Wide-Field Infrared Survey Explorer. I. Characterizing WISE-Selected AGN in COSMOS
• Initial Performance of the NEOWISE Reactivation Mission
• Spectral Classification and Redshift Measurement for the SDSS-III Baryon Oscillation Spectroscopic Survey
• The SuperCOSMOS Sky Survey. Paper I: Introduction and Description
• The Mid-IR Properties of Starburst Galaxies from Spitzer-IRS Spectroscopy
• Using the Bright Ultra-Hard XMM-Newton Survey to define an IR selection of luminous AGN based on WISE colours
• Galaxy And Mass Assembly (GAMA): Mid-Infrared Properties and Empirical Relations from $WISE$
• 2MASS Photometric Redshift catalog: a comprehensive three-dimensional census of the whole sky
• Photometric redshifts for the SDSS Data Release 12
• Characterizing the Mid-IR Extragalactic Sky with WISE and SDSS
• Identification of 1.4 Million AGNs in the Mid-Infrared using WISE Data
• The AllWISE Motion Survey and The Quest for Cold Subdwarfs
• An all-sky Support Vector Machine selection of WISE YSO Candidates
• The weirdest SDSS galaxies: results from an outlier detection algorithm
• WISE x SuperCOSMOS photometric redshift catalog: 20 million galaxies over 3pi steradians
• Full-depth Coadds of the WISE and First-year NEOWISE-Reactivation Images
• Galaxy and Mass Assembly (GAMA): Exploring the WISE Cosmic Web in G12
• The AllWISE Motion Survey, Part 2
• The Angular Clustering of WISE-Selected AGN: Different Haloes for Obscured and Unobscured AGN
• Multi-color Classification in the Calar Alto Deep Imaging Survey
• Star-Galaxy Classification in Multi-Band Optical Imaging
• Star-galaxy separation strategies for WISE-2MASS all-sky infrared galaxy catalogs
• The VIMOS Public Extragalactic Redshift Survey (VIPERS). A Support Vector Machine classification of galaxies, stars and AGNs
• Photometric classification of emission line galaxies with Machine Learning methods
• Automated Clustering Algorithms for Classification of Astronomical Objects
• Machine-learning identification of galaxies in the WISExSuperCOSMOS all-sky catalogue
• Star-galaxy separation by far-infrared color-color diagrams for the AKARI FIS All-Sky Survey (Bright Source Catalogue Version beta-1)
• Hyper-luminous Reddened Broad-Line Quasars at z~2 from the VISTA Hemisphere Survey and WISE All Sky Survey
• Exploring the 2MASS Extended and Point Source Catalogs with Clustering Redshifts
• Towards automatic classification of all WISE sources
• Classifying structures in the ISM with Support Vector Machines: the G16.05-0.57 supernova remnant
• Normal Nearby Galaxies
• Star-galaxy separation in the AKARI NEP Deep Field
• Luminous Red Galaxies: Selection and classification by combining optical and infrared photometry
• Of Genes and Machines: application of a combination of machine learning tools to astronomy datasets
• Clustering of the AKARI NEP Deep Field 24 $\mu$m selected galaxies

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