DocumentCode :
3181523
Title :
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
Link To Document :
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