首页|Reports Summarize Intelligent Systems Study Results from Liaoning Technical Univ ersity (Obmi: Oversampling Borderline Minority Instances By a Two-stage Tomek Li nk-finding Procedure for Class Imbalance Problem)
Reports Summarize Intelligent Systems Study Results from Liaoning Technical Univ ersity (Obmi: Oversampling Borderline Minority Instances By a Two-stage Tomek Li nk-finding Procedure for Class Imbalance Problem)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning - In telligent Systems have been presented. According to news reporting originating f rom Huludao, People’s Republic of China, by NewsRx correspondents, research stat ed, “Mitigating the impact of class imbalance datasets on classifiers poses a ch allenge to the machine learning community. Conventional classifiers do not perfo rm well as they are habitually biased toward the majority class.” Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Foundation of Liaoni ng Province Education Administration, PhD Startup Foundation of Liaoning Technic al University.
HuludaoPeople’s Republic of ChinaAsi aIntelligent SystemsMachine LearningLiaoning Technical University
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