Title :
A Hierarchical Fuzzy Clustering Algorithm
Author :
Li, Ling-Juan ; Liang, Yu-Long
Author_Institution :
Coll. of Comput., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Abstract :
A Hierarchical Fuzzy Clustering Algorithm is put forward to overcome the limitation of Fuzzy C-Means (FCM) algorithm. HFC discovers the high concentrated data areas by the agglomerative hierarchical clustering method quickly, analyzes and merges the data areas, and then uses the evaluation function to find the optimum clustering scheme. Experimental results indicate that HFC has higher clustering efficiency and precision.
Keywords :
fuzzy set theory; pattern clustering; statistical analysis; unsupervised learning; agglomerative hierarchical clustering method; data areas; fuzzy C-means algorithm; hierarchical fuzzy clustering algorithm; unsupervised learning; Algorithm; Fuzzy Clustering; Hierarchical Clustering;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622258
