Model-Based Clustering by Probabilistic Self-Organizing Maps

@article{Cheng2009ModelBasedCB,
  title={Model-Based Clustering by Probabilistic Self-Organizing Maps},
  author={Shih-Sian Cheng and Hsin-Chia Fu and Hsin-Min Wang},
  journal={IEEE Transactions on Neural Networks},
  year={2009},
  volume={20},
  pages={805-826}
}
In this paper, we consider the learning process of a probabilistic self-organizing map (PbSOM) as a model-based data clustering procedure that preserves the topological relationships between data clusters in a neural network. Based on this concept, we develop a coupling-likelihood mixture model for the PbSOM that extends the reference vectors in Kohonen's self-organizing map (SOM) to multivariate Gaussian distributions. We also derive three expectation-maximization (EM)-type algorithms, called… CONTINUE READING
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