首页|Study Data from University of Arizona Update Understanding of Machine Learning ( Spectroscopic Confirmation of Obscured Agn Populations From Unsupervised Machine Learning)
Study Data from University of Arizona Update Understanding of Machine Learning ( Spectroscopic Confirmation of Obscured Agn Populations From Unsupervised Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According tonews reporting out of Tucson, Arizona, by NewsRx editors, research stated, “We present the result ofa spectroscopic campa ign targeting active galactic nucleus (AGN) candidates selected using a novelun supervised machine-learning (ML) algorithm trained on optical and mid-infrared p hotometry. AGNcandidates are chosen without incorporating prior AGN selection c riteria and are fainter, redder, and morenumerous, similar to 340 AGN deg(-2), than comparable photometric and spectroscopic samples.”
TucsonArizonaUnited StatesNorth an d Central AmericaCyborgsEmerging TechnologiesMachine LearningUniversity of Arizona
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