Hierarchical Clustering Using Mutual Information

  title={Hierarchical Clustering Using Mutual Information},
  author={Alexander Kraskov and Harald St{\"o}gbauer and Ralph G. Andrzejak and Peter Grassberger},
– We present a conceptually simple method for hierarchical clustering of data called mutual information clustering (MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects X, Y , and Z is equal to the sum of the MI between X and Y , plus the MI between Z and the combined object (XY ). We use this both in the Shannon (probabilistic) version of information theory and in the Kolmogorov (algorithmic) version. We apply… CONTINUE READING
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