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Proceedings of International Joint Conference on Neural Networks, Montreal, Canada, July 31 -August 4, 2005 0-7803-9048-2/05/$20.00 2005 IEEE
 

Summary: Proceedings of International Joint Conference on Neural Networks, Montreal, Canada, July 31 - August 4, 2005
0-7803-9048-2/05/$20.00 ©2005 IEEE
Feature Ranking using Supervised Neural Gas and
Informational Energy
Razvan Andonie
Computer Science Department
Central Washington University, Ellensburg, USA
Email: andonie@cwu.edu
Angel Catłaron
Department of Electronics and Computers
Transylvania University of Brasłov, Romania
Email: cataron@vega.unitbv.ro
Abstract-- In this paper we use the maximization of Onicescu's
informational energy as a criteria for computing the relevances
of input features. This adaptive relevance determination is
used in combination with the neural gas and the generalized
relevance LVQ algorithms. The idea of applying the neural gas
neighborhood cooperation technique to improve the generalized
relevance LVQ is due to Hammer et al. and is best described
in [1]. Our approach gives an alternative way for determining

  

Source: Andonie, Razvan - Department of Computer Science, Central Washington University

 

Collections: Computer Technologies and Information Sciences