首页|New Findings from Jilin University Describe Advances in Machine Learning (High-p erformance Imbalanced Learning Ensembles of Decision Trees for Detecting Mineral ization Anomalies From Geochemical Exploration Data)
New Findings from Jilin University Describe Advances in Machine Learning (High-p erformance Imbalanced Learning Ensembles of Decision Trees for Detecting Mineral ization Anomalies From Geochemical Exploration Data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting from Jilin, People’s Republ ic of China, by NewsRx journalists, research stated, “How to effectively detect geochemical anomalies associated with mineralization is a challenging task due t o the extreme classimbalance of geochemical exploration data. To address this c hallenge, various machine learning techniques have been employed to detect geoch emical anomalies associated with mineralization.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
JilinPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningJilin University
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