Self Organized Dynamic Tree Neural Network

Authors:
Juan F. Paz;Sara Rodríguez;Javier Bajo;Juan M. Corchado;Vivian López
Affiliations:
Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España 37008 and Department of Computer Science and Automation, University of Salamanca, Salamanca, Sp ...;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España 37008 and Department of Computer Science and Automation, University of Salamanca, Salamanca, Sp ...;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España 37008 and Department of Computer Science and Automation, University of Salamanca, Salamanca, Sp ...;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España 37008 and Department of Computer Science and Automation, University of Salamanca, Salamanca, Sp ...;Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, España 37008 and Department of Computer Science and Automation, University of Salamanca, Salamanca, Sp ...
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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Abstract

Cluster analysis is a technique used in a variety of fields. There are currently various algorithms used for grouping elements that are based on different methods including partitional, hierarchical, density studies, probabilistic, etc. This article will present the SODTNN, which can perform clustering by integrating hierarchical and density-based methods. The network incorporates the behavior of self-organizing maps and does not specify the number of existing clusters in order to create the various groups.