Maximal Margin Estimation with Perceptron-Like Algorithm

Authors:
Marcin Korzeń;Przemysław Klęsk
Affiliations:
Faculty of Computer Science and Information Systems, Szczecin University of Technology, Szczecin, Poland 71-210;Faculty of Computer Science and Information Systems, Szczecin University of Technology, Szczecin, Poland 71-210
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

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Abstract

In this paper we propose and analyse a 茂戮驴-margin generalisation of the perceptron learning algorithm of Rosenblatt. The difference between the original approach and the 茂戮驴-margin approach is only in the update step. We consider the behaviour of such a modified algorithm in both separable and non-separable case and also when the 茂戮驴-margin is negative. We give the convergence proof of such a modified algorithm, similar to the classical proof by Novikoff. Moreover we show how to change the margin of the update step in the progress of the algorithm to obtain the maximal possible margin of separation. In application part, we show the connection of the maximal margin of separation with SVM methods.