Information-Theoretic Distance Measures for Clustering Validation: Generalization and Normalization

@article{Luo2009InformationTheoreticDM,
  title={Information-Theoretic Distance Measures for Clustering Validation: Generalization and Normalization},
  author={Ping Luo and Hui Xiong and Guoxing Zhan and Junjie Wu and Zhongzhi Shi},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2009},
  volume={21},
  pages={1249-1262}
}
This paper studies the generalization and normalization issues of information-theoretic distance measures for clustering validation. Along this line, we first introduce a uniform representation of distance measures, defined as quasi-distance, which is induced based on a general form of conditional entropy. The quasi-distance possesses three properties: symmetry, the triangle law, and the minimum reachable. These properties ensure that the quasi-distance naturally lends itself as the external… CONTINUE READING
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