Approximate Analytical Bootstrap Averages for Support Vector Classifiers

Part of Advances in Neural Information Processing Systems 16 (NIPS 2003)

Authors

Dörthe Malzahn, Manfred Opper

Abstract

We compute approximate analytical bootstrap averages for support vec- tor classification using a combination of the replica method of statistical physics and the TAP approach for approximate inference. We test our method on a few datasets and compare it with exact averages obtained by extensive Monte-Carlo sampling.