Title :
Mining VIP Based on an Improved Hierarchical Clustering Method
Author :
Bin Nie ; Du, Jianqiang ; Liu, Hongnin ; Xu, Guoliang ; Wang, Zhuo ; Zhu, Mingfeng ; Zhang, Qiyun
Author_Institution :
Sch. of Comput., Jiang Xi Univ. of traditional Chinese Med., Nanchang, China
fDate :
Nov. 30 2009-Dec. 1 2009
Abstract :
Traditional hierarchical clustering (HC) methods which always fail to deal with very large databases or high dimensional spaces. In the paper, arithmetic mean, arithmetic mean ratios and so on are introduced. Variable trend, data preprocessing for database based on variable trend, and mining VIP (variable important in M/Z, or called typical characteristic) based on an improved hierarchical clustering method is put forward. It was proved to be feasible and effective to mining VIP according necessity after tested.
Keywords :
biology computing; data mining; pattern clustering; very large databases; arithmetic mean; arithmetic mean ratios; data preprocessing; improved hierarchical clustering method; metabolomics; mining VIP; typical characteristic; variable trend; very large databases; Arithmetic; Clustering methods; Data mining; Data preprocessing; Databases; Magnetic analysis; Medical diagnostic imaging; Mice; Nuclear magnetic resonance; Pattern recognition; arithmetic mean; hierarchical clustering; mining VIP; variable trend;
Conference_Titel :
Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3888-4
DOI :
10.1109/KAM.2009.172
