Material Detail

Stopping Conditions for Exact Computation of Leave-One-Out Error in Support Vector Machines

Stopping Conditions for Exact Computation of Leave-One-Out Error in Support Vector Machines

This video was recorded at 25th International Conference on Machine Learning (ICML), Helsinki 2008. We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-One-Out error computation. The stopping condition guarantees that the output on an intermediate SVM solution is identical to the output of the optimal SVM solution with one data point excluded from the training set. A simple augmentation of a general SVM training algorithm allows one to use a stopping criterion equivalent to the proposed sufficient condition. A comprehensive experimental evaluation of our method shows consistent speedup of the exact LOO computation by our method, up to the factor of 13 for the linear kernel. The new algorithm can be seen as an... Show More

Quality

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

More about this material

Browse...

Disciplines with similar materials as Stopping Conditions for Exact Computation of Leave-One-Out Error in Support Vector Machines
Other materials like Stopping Conditions for Exact Computation of Leave-One-Out Error in Support Vector Machines

Comments

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