Topology-Preserving Map Formation Achieved with a Genetic Algorithm and its Application in Cluster Analysis

Mu-Chun Su; Hsiao-Te Chang

doi:10.6180/jase.1999.2.1.04

Topology-Preserving Map Formation Achieved with a Genetic Algorithm and its Application in Cluster Analysis

Electrical Engineering

Mu-Chun Su¹ and Hsiao-Te Chang¹

¹Department of Electrical Engineering Tamkang University Tamsui, 251, Taiwan, R.O.C.

Received: April 12, 1999
Accepted: May 31, 1999
Publication Date: May 31, 1999

Download Citation: ||https://doi.org/10.6180/jase.1999.2.1.04

ABSTRACT

In this paper we propose an efficient method for measuring the degree of topology preservation. Based on the method we apply genetic algorithms (GAs) in two stages to form a topologically ordered feature map. We then use a special method to interprete an SOFM formed by the proposed genetic-algorithm-based method to estimate the number and the locations of clusters from a multidimensional data set without labeling information. Two data sets are used to illustrate the performance of the proposed methods.

Keywords: Cluster Analysis, Genetic Algorithms, Neural Networks, Self-Organizing Feature Maps

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