DocumentCode :
2649317
Title :
Cluster label aligning algorithm based on programming model
Author :
Fan Haixiong ; Liu Fuxian ; Xia Lu
Author_Institution :
Missile Inst., Air force Eng. Univ., Xi´an, China
fYear :
2012
fDate :
23-25 May 2012
Firstpage :
1768
Lastpage :
1772
Abstract :
Cluster ensembles can improve single clusters performance effectively, but the cluster labels are not fused directly due to lack of prior information supervising. Based on analysis and research on existing methods, label aligning was convert to the assign problem. And two cluster label aligning algorithms were proposed, which use overlap similarity rate as the coefficient matrix, Hungary and implicit enumeration algorithm as basic algorithms. Lastly, experimental simulation and capability analysis were completed, and results prove the availability and applicability of the new algorithms.
Keywords :
matrix algebra; pattern clustering; Hungary enumeration algorithm; cluster ensembles; cluster label aligning algorithm; cluster labels; clusters performance; coefficient matrix; experimental simulation; implicit enumeration algorithm; programming model; Algorithm design and analysis; Analytical models; Approximation algorithms; Clustering algorithms; Matrix converters; Programming; Vectors; Assignment problem; Cluster ensemble; Hungary algorithm; Implicit enumeration algorithm; Label aligning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
Type :
conf
DOI :
10.1109/CCDC.2012.6243019
Filename :
6243019
Link To Document :
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