首页|Studies from Guizhou Minzu University Provide New Data on Support Vector Machine s (Weighted Intuitionistic Fuzzy Twin Support Vector Machines With Truncated Pin ball Loss)
Studies from Guizhou Minzu University Provide New Data on Support Vector Machine s (Weighted Intuitionistic Fuzzy Twin Support Vector Machines With Truncated Pin ball Loss)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on have been pub lished. According to news originating from Guiyang, People’s Republic of China, by NewsRx correspondents, research stated, “Although an intuitionistic fuzzy twi n support vector machines (IFTSVM) can reduce the impact of noise and outliers i n classification problems, it is sensitive to noise, is unstable in resampling a nd lacks sparsity.” Funders for this research include National Natural Science Foundation of China; Natural Science Foundation of Guizhou Province; Natural Science Research Project of Department of Education of Guizhou Province.
Guizhou Minzu UniversityGuiyangPeopl e’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupport Ve ctor MachinesVector Machines
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