2018
DOI: 10.1093/mnras/sty3359
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A machine learning approach for identification and classification of symbiotic stars using 2MASS and WISE

Abstract: In this second paper in a series of papers based on the most-up-to-date catalogue of symbiotic stars (SySts), we present a new approach for identifying and distinguishing SySts from other H α emitters in photometric surveys using machine learning algorithms such as classification tree, linear discriminant analysis, and K-nearest neighbour. The motivation behind of this work is to seek for possible colour indices in the regime of near-and mid-infrared covered by the 2MASS and WISE surveys. A number of diagnosti… Show more

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Cited by 50 publications
(64 citation statements)
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“…S-type symbiotic stars (Akras et al 2019;Corradi et al 2008). The properties of these systems, which we identify as symbiotic systems in Draco dSph are discussed in the following.…”
Section: Symbiotic Stars In the Draco Dsphmentioning
confidence: 99%
“…S-type symbiotic stars (Akras et al 2019;Corradi et al 2008). The properties of these systems, which we identify as symbiotic systems in Draco dSph are discussed in the following.…”
Section: Symbiotic Stars In the Draco Dsphmentioning
confidence: 99%
“…Following Mukai et al (), as the SySts without shell burning do not have prominent emission lines, all SySt catalogues could preferentially consist of the shell‐burning systems because most surveys are still based on spectroscopic methods. Just recently, new approaches and techniques are explored in order to identify new systems (e.g., machine‐learning algorithms; Akras et al ).…”
Section: X‐ray Emission Of Symbiotic Variable Starsmentioning
confidence: 99%
“…-see, e.g., Figs. 1 & 2 in Corradi et al 2008;Akras et al 2019b), no photometric diagnostic tool has so far demonstrated the power to unambiguously identify a SySt, thus making the recourse to costly spectroscopic follow-up still inescapable.…”
Section: Introductionmentioning
confidence: 99%