首页|New Findings from University Juarez Autonoma of Tabasco in the Area of Support V ector Machines Described (Asymptotic Behavior of Some Multicategory Classificati on Methods for High-dimensional Data)
New Findings from University Juarez Autonoma of Tabasco in the Area of Support V ector Machines Described (Asymptotic Behavior of Some Multicategory Classificati on Methods for High-dimensional Data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning - Sup port Vector Machines is the subject of a report. According to news reporting out of Tabasco, Mexico, by NewsRx editors, research stated, “We consider multicateg ory extensions of binary discrimination methods via one-versus-one (OVO) or one- versus-rest (OVR) methodologies, focusing on extensions of the binary classifica tion by linear mean difference (MD), support vector machine (SVM), maximal data piling (MDP), and distance weighted discrimination (DWD) via OVO, and the multic ategory extension of MD via OVR, in the context of high-dimensional and low samp le size (HDLSS) data. The asymptotic behavior of OVO-MD, OVO-SVM, OVO-MDP and OV ODWD is described when the dimension of the data increases and the sample size is fixed, in terms of the probabilities of correct classification of a new data point, finding sufficient conditions for the correct classification probabilitie s to converge to one as the dimension approaches infinity.”
TabascoMexicoNorth and Central Ameri caMachine LearningSupport Vector MachinesUniversity Juarez Autonoma of Tab asco
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