PARTCAT: A Subspace Clustering Algorithm for High Dimensional Categorical Data

  title={PARTCAT: A Subspace Clustering Algorithm for High Dimensional Categorical Data},
  author={Guojun Gan and Jianhong Wu and Zijiang Yang},
  journal={The 2006 IEEE International Joint Conference on Neural Network Proceedings},
A new subspace clustering algorithm, PARTCAT, is proposed to cluster high dimensional categorical data. The architecture of PARTCAT is based on the recently developed neural network architecture PART, and a major modification is provided in order to deal with categorical attributes. PARTCAT requires less number of parameters than PART, and in particular, PARTCAT does not need the distance parameter that is needed in PART and is intimately related to the similarity in each fixed dimension. Some… CONTINUE READING
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