MinOver Revisited for Incremental Support-Vector-Classification

The well-known and very simple MinOver algorithm is reformulated for incremental support vector classification with and without kernels. A modified proof for its O(t-1/2 ) convergence is presented, with t as the number of training steps. Based on this modified proof it is shown that even a convergence of at least O(t-1 ) is given. This new convergence bound for MinOver is confirmed by computer experiments on artificial data sets. The computational effort per training step scales as O(N) with the number N of training patterns.

• Type: Conference
• Year: 2004
• Where: DAGM
• Authors: Thomas Martinetz
• Keywords: Convergence, DAGM 2004, Image Processing, Modified Proof, Training Step