DECA: A Discrete-Valued Data Clustering Algorithm

  title={DECA: A Discrete-Valued Data Clustering Algorithm},
  author={Andrew K. C. Wong and David C. C. Wang},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
This paper presents a new clustering algorithm for analyzing unordered discrete-valued data. This algorithm consists of a cluster initiation phase and a sample regrouping phase. The first phase is based on a data-directed valley detection process utilizing the optimal second-order product approximation of high-order discrete probability distribution, together with a distance measure for discrete-valued data. As for the second phase, it involves the iterative application of the Bayes' decision… CONTINUE READING


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