Some Competitive Learning Methods

This report has the purpose of describing several algorithms from the literature all related to competitive learning. A uniform terminology is used for all methods. Moreover, identical examples are provided to allow a qualitative comparisons of the methods. The on-line version 1 of this document contains hyperlinks to Java implementations of several of the discussed methods. 1 http://www.neuroinformatik.ruhr-uni-bochum.de/ini/VDM/research/gsn/JavaPaper/ Contents 1 Introduction 3 2 Common Properties & Notational Conventions 4 3 Goals of Competitive Learning 7 3.1 Error Minimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2 Entropy Maximization . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3 Feature Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.4 Other Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 4 Hard Competitive Learning 10 4.1 Batch Update: LBG . . . . . . . . . . . . . . . . . . . . . . . . . . ..