首页|Research Data from Ningbo University Update Understanding of Support Vector Mach ines (Multi-view Hypergraph Regularized Lp Norm Least Squares Twin Support Vecto r Machines for Semisupervised Learning)
Research Data from Ningbo University Update Understanding of Support Vector Mach ines (Multi-view Hypergraph Regularized Lp Norm Least Squares Twin Support Vecto r Machines for Semisupervised Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Support Vector Machines. According to news reportingfrom Ningbo, People’s Republic of China, by NewsRx journalists, research stated, “In recent years, multiviewsemi -supervised learning has gradually become a popular research direction. The clas sic binaryclassification methods in this field are multi-view Laplacian support vector machines (MvLapSVM) andmulti-view Laplacian twin support vector machine s (MvLapTSVM), which extend semisupervised supportvector machine to multi-view learning.”
NingboPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupervised LearningSupport Vector M achinesVector MachinesNingbo University
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