LEGClust—A Clustering Algorithm Based on Layered Entropic Subgraphs

@article{Santos2008LEGClustACA,
  title={LEGClust—A Clustering Algorithm Based on Layered Entropic Subgraphs},
  author={Jorge M. Santos and Joaquim Marques de S{\'a} and Lu{\'i}s A. Alexandre},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2008},
  volume={30},
  pages={62-75}
}
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity measures are distance measures. The derived proximity matrices can be used to build graphs, which provide the basic structure for some clustering methods. We present here a new proximity matrix based on an entropic measure and also a clustering algorithm (LEGCIust) that builds layers of subgraphs based on this matrix and… CONTINUE READING
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