Open AccessImproving fuzzy C‐means clustering algorithm based on a density‐induced distance measure
Author(s) -
Lu Chunhong,
Xiao Shaoqing,
Gu Xiaofeng
Publication year - 2014
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2014.0053
Subject(s) - measure (data warehouse) , cluster analysis , computer science , fuzzy logic , fuzzy clustering , algorithm , data mining , artificial intelligence
The authors report an improved fuzzy C‐means algorithm in comparison with the conventional one by employing a density‐induced distance metric based on a novel calculation method of relative density degree. By using various synthetic and real data sets, the clustering performance of the proposed method is systematically studied and compared with that of the conventional one. The obtained results support the conclusion that this novel method does not only inherit good characteristics of the traditional one, but also possesses improved partitions.