Material Detail

The Limit of One-Class SVM

The Limit of One-Class SVM

This video was recorded at Workshop on Modelling in Classification and Statistical Learning, Eindhoven 2004. In this talk, I will present an analysis of the asymptotic behaviour of the One-Class support vector machine (SVM), a popular algorithm for outlier detection. I will show that One-Class SVM asymptotically estimates a truncated version of the density of the distribution generating the data, in the case where the Gaussian kernel is used with a well-calibrated decreasing bandwidth parameter, and the regularization parameter involved in the algorithm is held fixed as the training sample size goes to infinity.A long version of this work can be found at , in which extensions to the 2-class case and to more general convex loss functions are considered.


  • User Rating
  • Comments
  • Learning Exercises
  • Bookmark Collections
  • Course ePortfolios
  • Accessibility Info

More about this material


Log in to participate in the discussions or sign up if you are not already a MERLOT member.