Topology-Based Hierarchical Clustering of Self-Organizing Maps

  title={Topology-Based Hierarchical Clustering of Self-Organizing Maps},
  author={Kadim Tasdemir and Pavel Milenov and Brooke Tapsall},
  journal={IEEE Transactions on Neural Networks},
A powerful method in the analysis of datasets where there are many natural clusters with varying statistics such as different sizes, shapes, density distribution, overlaps, etc., is the use of self-organizing maps (SOMs). However, further processing tools, such as visualization and interactive clustering, are often necessary to capture the clusters from the learned SOM knowledge. A recent visualization scheme (CONNvis) and its interactive clustering utilize the data topology for SOM knowledge… CONTINUE READING
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