Multivariate statistics: a practical approach
Multivariate statistics: a practical approach
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Self-organizing maps
GTM: the generative topographic mapping
Neural Computation
Hierarchical GTM: Constructing Localized Nonlinear Projection Manifolds in a Principled Way
IEEE Transactions on Pattern Analysis and Machine Intelligence
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Two topographic maps for data visualisation
Data Mining and Knowledge Discovery
Clustering with reinforcement learning
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Quantization errors in the harmonic topographic mapping
SIP'06 Proceedings of the 5th WSEAS international conference on Signal processing
A family of novel clustering algorithms
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
A novel construction of connectivity graphs for clustering and visualization
WSEAS Transactions on Computers
Adjusting Fuzzy Similarity Functions for use with standard data mining tools
Journal of Systems and Software
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We [6, 7] have recently investigated several families of clustering algorithms. In this paper, we show how a novel similarity function can be integrated into one of our algorithms as a method of performing clustering and show that the resulting method is superior to existing methods in that it canbe shown to reliably find a globally optimal clustering rather than local optima which other methods often find. We also extend the method to perform topology preserving mappings and show the results of such mappings on artificial and real data.