Approximate Analytical Bootstrap Averages for Support Vector Classifiers

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

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Dörthe Malzahn, Manfred Opper


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.