This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2009 WRI World Congress on Computer Science and Information Engineering
A Novel Fuzzy Based Classification for Data Mining Using Fuzzy Discretization
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
Data mining is a process to discover useful, possibly unexpected, patterns from the large set of data and widely used in the large information processing applications. Classification is used to classify the data into a set of classes based on some attributes for further processing. Real world application contains very large,imprecise and noisy data. In this case, the knowledge representation need some linguistic term instead of discrete value. In such a scenario fuzzy logic based processing is a natural choice. In this paper, we propose an algorithm for classification using fuzzy approach,which performs class dependent fuzzy discretization.The continuous numeric data is converted in linguistic form which helps in fuzzy classification. The proposed method is compared with standard non-fuzzy discretization techniques where class-attribute relationship is not considered and intervals are predefined. Simulation results show the improved performance of the proposed method.
Index Terms:
Data Mining (DM), Fuzzy based Classification, Interval discretization, Fuzzy discretization
Citation:
Rupa G. Mehta, Dipti P. Rana, Mukesh A. Zaveri, "A Novel Fuzzy Based Classification for Data Mining Using Fuzzy Discretization," csie, vol. 3, pp.713-717, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
Usage of this product signifies your acceptance of the Terms of Use.