Self-Organizing Maps
2005 Special Issue: Cross-entropy embedding of high-dimensional data using the neural gas model
Neural Networks - 2005 Special issue: IJCNN 2005
Two level minimization in multidimensional scaling
Journal of Global Optimization
Handbook of Data Visualization (Springer Handbooks of Computational Statistics)
Handbook of Data Visualization (Springer Handbooks of Computational Statistics)
Dimension Reduction and Data Visualization Using Neural Networks
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Interactive visualization and analysis of hierarchical neural projections for data mining
IEEE Transactions on Neural Networks
Influence of learning rates and neighboring functions on self-organizing maps
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
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In this paper, we present a comparative analysis of a combination of two vector quantization methods (self-organizing map and neural gas), based on a neural network and multidimensional scaling that is used for visualization of codebook vectors obtained by vector quantization methods. The dependence of computing time on the number of neurons, the ratio between the number of neuron-winners and that of all neurons, quantization and mapping qualities, and preserving of a data structure in the mapping image are investigated.