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Nu-Support Vector Machine as Conditional Value-at-Risk Minimization
Akiko Takeda
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Oznake: computer science;machine learning;kernel methods;support vector machines
The nu-support vector classification (nu-SVC) algorithm was shown to work well and provide intuitive interpretations, e.g., the parameter nu roughly specifies the fraction of support vectors. Although nu corresponds to a fraction, it cannot take the entire range between 0 and 1 in its original form. ...
Leto: 2008 Vir: videolectures.net
Št. zadetkov: 1
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