Abstract
Abstract The aim of this work is to create a new catalog of reliable active galactic nucleus (AGN) candidates selected from the AKARI NEP-Deep field. Selection of the AGN candidates was done by applying a fuzzy support vector machine algorithm, which allows the incorporation of 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 275 previously unclassified AGN candidates was prepared.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.