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

Volume

3

fYear

2009

fDate

Nov. 30 2009-Dec. 1 2009

Firstpage

323

Lastpage

326

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3888-4

Type

conf

DOI

10.1109/KAM.2009.172

Filename

5362300