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A Note on Linear SVM in Gaussian Classes
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 Title & Authors
A Note on Linear SVM in Gaussian Classes
Jeon, Yongho;
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The linear support vector machine(SVM) is motivated by the maximal margin separating hyperplane and is a popular tool for binary classification tasks. Many studies exist on the consistency properties of SVM; however, it is unknown whether the linear SVM is consistent for estimating the optimal classification boundary even in the simple case of two Gaussian classes with a common covariance, where the optimal classification boundary is linear. In this paper we show that the linear SVM can be inconsistent in the univariate Gaussian classification problem with a common variance, even when the best tuning parameter is used.
Consistency for classification;Fisher consistency;Gaussian linear discriminant analysis;support vector machines;
 Cited by
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