Title :
Extension of HAC clustering method with quality threshold
Author :
Bednarik, László ; Kovács, László
Author_Institution :
Dept. of Inf. Technol., Univ. of Miskolc, Miskolc, Hungary
Abstract :
Most of the standard clustering methods meet only partially the base requirement of clustering, i.e. the inter-cluster similarity is larger than the intra-cluster similarity. Only the BIRCH and QT algorithms consider the similarity threshold parameter. The paper provides an extension of HAC clustering method to include the quality threshold parameter.
Keywords :
pattern clustering; BIRCH algorithm; HAC clustering method; QT algorithm; hierarchical agglomerative clustering; intercluster similarity; intracluster similarity; quality threshold; similarity threshold parameter; Clustering algorithms; Clustering methods; Complexity theory; Heuristic algorithms; Informatics; Intelligent systems; Junctions;
Conference_Titel :
Intelligent Systems and Informatics (SISY), 2011 IEEE 9th International Symposium on
Conference_Location :
Subotica
Print_ISBN :
978-1-4577-1975-2
DOI :
10.1109/SISY.2011.6034333
