clustering mixed data by fast search and find of density peaks

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ID: 191761
2017
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Abstract
Aiming at the mixed data composed of numerical and categorical attributes, a new unified dissimilarity metric is proposed, and based on that a new clustering algorithm is also proposed. The experiment result shows that this new method of clustering mixed data by fast search and find of density peaks is feasible and effective on the UCI datasets.
Reference Key
liu2017mathematicalclustering Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Shihua Liu;Bingzhong Zhou;Decai Huang;Liangzhong Shen
Journal journal of power sources
Year 2017
DOI
10.1155/2017/5060842
URL
http://dx.doi.org/10.1155/2017/5060842
Keywords
civil engineering (general)mathematics engineering (general)

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