Lazy Self-Organizing Map and its behaviors

@article{Haraguchi2008LazySM,
  title={Lazy Self-Organizing Map and its behaviors},
  author={Taku Haraguchi and Haruna Matsushita and Yoshifumi Nishio},
  journal={2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={2275-2280}
}
  • Taku Haraguchi, H. Matsushita, Y. Nishio
  • Published 2008
  • Computer Science
  • 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)
The Self-Organizing Map (SOM) is a famous algorithm for the unsupervised learning and visualization introduced by Teuvo Kohonen. This study proposes the Lazy Self-Organizing Map (LSOM) algorithm which reflects the world of worker ants. In LSOM, three kinds of neurons exist: worker neurons, lazy neurons and indecisive neurons. We apply LSOM to various input data set and confirm that LSOM can obtain a more effective map reflecting the distribution state of the input data than the conventional SOM… Expand
Behaviors of Lazy Self-Organizing Map Considering Lazy-Neuron Rate
The Self-Organizing Map (SOM) is unsupervised neural networks introduced by Kohonen. The SOM attracts attentions for clustering in these years. In the previous study, we have proposed the LazyExpand
Lazy Self-Organizing Map Considering Lazy-Neuron Rate for Effective Self-Organization
TLDR
An improved LSOM, whose learning rate depends on each neuron’s character, lazy-neuron rate and time is proposed and applied to various input data set and investigated its effectiveness using three measurements. Expand

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