首页|New Findings from Hunan Normal University in Computational Intelligence Provides New Insights (Attribute Reduction for Heterogeneous Data By Hybrid Neighborhood Graph Structure and Neighbor Inconsistent Pair Selection)
New Findings from Hunan Normal University in Computational Intelligence Provides New Insights (Attribute Reduction for Heterogeneous Data By Hybrid Neighborhood Graph Structure and Neighbor Inconsistent Pair Selection)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning - Comp utational Intelligence is now available. According to news reporting originating in Changsha, People’s Republic of China, by NewsRx journalists, research stated , “As an effective means of data processing, the rough set model simulates human cognition by partitioning objects into multiple granules. Currently, the rough set model is widely used in attribute reduction.”
ChangshaPeople’s Republic of ChinaAsiaComputational IntelligenceMachine LearningHunan Normal University
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