Crowds´ Classification Using Hierarchical Cluster, Rough Sets, Principal Component Analysis and Its Combination

Author

Nie, Bin ; Du, Jianqiang ; Liu, Hongning ; Xu, Guoliang ; Wang, Zhuo ; He, Yan ; Li, Bingtao

Author_Institution

Sch. of Comput., Jiang Xi Univ. of Traditional Chinese Med., Nanchang, China

Volume

1

fYear

2009

fDate

25-27 Dec. 2009

Firstpage

287

Lastpage

290

Abstract

13 kind of nationalities crowds´ data classification using hierarchical cluster (HC), rough sets (RS), principal component analysis (PCA) and its combination, the result shows: first, rough sets and principal component analysis can dimensionality reduction and de-noising; second, hierarchical cluster after rough sets (RSHC), principal component analysis after rough sets (PCARS), principal component analysis after principal component analysis (PCAPCA), hierarchical cluster after principal component analysis (HCPCA), rough sets after principal component analysis (PCARS) are similarly result. Then, according to different practical application select different methods or combinative methods, which can maximize their advantages and minimize their disadvantages.

Keywords

pattern classification; pattern clustering; principal component analysis; rough set theory; PCA; crowd classification; dimensionality denoising; dimensionality reduction; hierarchical cluster after principal component analysis; hierarchical cluster after rough sets; principal component analysis after principal component analysis; principal component analysis after rough sets; rough sets after principal component analysis; Application software; Computer applications; Computer science education; Data mining; Educational institutions; Information analysis; Information systems; Principal component analysis; Rough sets; Uncertainty; combination; hierarchical cluster (HC); principal component analysis (PCA); rough sets (RS);

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on

Conference_Location

Chongqing

Print_ISBN

978-0-7695-3930-0

Electronic_ISBN

978-1-4244-5423-5

Type

conf

DOI

10.1109/IFCSTA.2009.75

Filename

5385079