DocumentCode
2858262
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
Volume
12
fYear
2010
fDate
22-24 Oct. 2010
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICCASM.2010.5622258
Filename
5622258
Link To Document