A comparison of the classification capabilities of the 1-dimensional kohonen neural network with two pratitioning and three hierarchical cluster analysis algorithms

Waller, N. G., Kaiser, H. A., Illian, J. B. and Manry, M. (1998) A comparison of the classification capabilities of the 1-dimensional kohonen neural network with two pratitioning and three hierarchical cluster analysis algorithms. Psychometrika, 63(1), pp. 5-22. (doi:10.1007/BF02295433)

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Abstract

Neural Network models are commonly used for cluster analysis in engineering, computational neuroscience, and the biological sciences, although they are rarely used in the social sciences. In this study we compare the classification capabilities of the 1-dimensional Kohonen neural network with two partitioning (Hartigan and Späthk-means) and three hierarchical (Ward's, complete linkage, and average linkage) cluster methods in 2,580 data sets with known cluster structure. Overall, the performance of the Kohonen networks was similar to, or better than, the performance of the other methods.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Illian, Professor Janine
Authors: Waller, N. G., Kaiser, H. A., Illian, J. B., and Manry, M.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Psychometrika
Publisher:Springer
ISSN:0033-3123
ISSN (Online):1860-0980

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