Regularization approaches for support vector machines with applications to biomedical data

  • Daniel Lopez-Martinez
  • Published 2017

Abstract

The support vector machine (SVM) is a widely used machine learning tool for classification based on statistical learning theory. Given a set of training data, the SVM finds a hyperplane that separates two different classes of data points by the largest distance. While the standard form of SVM uses L2-norm regularization, other regularization approaches are… (More)

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