TY - GEN

T1 - Stopping conditions for exact computation of leave-one-out error in support vector machines

AU - Franc, Vojtěch

AU - Laskov, Pavel

AU - Müller, Klaus Robert

PY - 2008

Y1 - 2008

N2 - 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 example of constructive guidance of an optimization algorithm towards achieving the best attainable expected risk at optimal computational cost.

AB - 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 example of constructive guidance of an optimization algorithm towards achieving the best attainable expected risk at optimal computational cost.

UR - http://www.scopus.com/inward/record.url?scp=56449124175&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=56449124175&partnerID=8YFLogxK

U2 - 10.1145/1390156.1390198

DO - 10.1145/1390156.1390198

M3 - Conference contribution

AN - SCOPUS:56449124175

SN - 9781605582054

T3 - Proceedings of the 25th International Conference on Machine Learning

SP - 328

EP - 335

BT - Proceedings of the 25th International Conference on Machine Learning

PB - Association for Computing Machinery (ACM)

T2 - 25th International Conference on Machine Learning

Y2 - 5 July 2008 through 9 July 2008

ER -