The aim of this work is to create a new catalog of reliable AGN candidates selected from the AKARI NEP-Deep field. Selection of the AGN candidates was done by applying a fuzzy SVM algorithm, which allows to incorporate measurement uncertainties into the classification process. The training dataset was based on the spectroscopic data available for selected objects in the NEP-Deep and NEP-Wide fields. The generalization sample was based on the AKARI NEP-Deep field data including objects without optical counterparts and making use of the infrared information only. A high quality catalog of previously unclassified 275 AGN candidates was prepared.
Cite
@article{arxiv.1902.04922,
title = {AGN selection in the AKARI NEP deep field with the fuzzy SVM algorithm},
author = {Artem Poliszczuk and Aleksandra Solarz and Agnieszka Pollo and Maciej Bilicki and Tsutomu T. Takeuchi and Hideo Matsuhara and Tomotsugu Goto and Toshinobu Takagi and Takehiko Wada and Yoichi Ohyama and Hitoshi Hanami and Takamitsu Miyaji and Nagisa Oi and Matthew Malkan and Kazumi Murata and Helen Kim and Jorge Díaz Tello},
journal= {arXiv preprint arXiv:1902.04922},
year = {2021}
}