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Universal clustering algorithm based on an adaptive density gradient
  • Wenke Li ,
  • Zhou Zhou
Wenke Li
Fuwai hospital, Fuwai hospital

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Zhou Zhou
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We proposed a universal clustering algorithm by constructing an adaptive density gradient. This algorithm showed no data preference, and performs well on data with arbitrary density, overlap and shape. In comparative experiments, it outperformed other state-of-the-art algorithms on all types of synthetic and real data.