DocumentCode :
519600
Title :
A classification method based on PAM algorithm and discrete preprocess
Author :
Yang, Huaizhen ; Li, Lei
Author_Institution :
Sch. of Bus., Guilin Univ. of Electron. Technol., Guilin, China
Volume :
2
fYear :
2010
fDate :
21-24 May 2010
Abstract :
Using clustering method to generate training set, and applying rough set theory to discretization preprocess, the classification accuracy can be improve well. This paper applied PAM clustering algorithm to constitute a training set from original sample, used a discrete algorithm that integrates Boolean logic with rough set theory to discretize the training set, and trained classifier by the discrete training set. When classification was carried out in the same data set, experimental results showed that compared to the RDDTE method only based on the PAM algorithm to preprocess, the classification accuracy based on the new method increased 15.5 percentage points at most. Besides, the new method selected a smaller amount of training set.
Keywords :
Boolean functions; pattern classification; pattern clustering; rough set theory; Boolean logic; PAM clustering algorithm; classification method; discrete preprocess; discrete training set; rough set theory; Boolean functions; Clustering algorithms; Clustering methods; Decision trees; Information systems; Information technology; Machine learning algorithms; Production; Set theory; Training data; PAM; cross validation; data discretization; heuristic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5821-9
Type :
conf
DOI :
10.1109/ICFCC.2010.5497346
Filename :
5497346
Link To Document :
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