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Front. Inform. Technol. Electron. Eng.  2011, Vol. 12 Issue (5): 379-386    DOI: 10.1631/jzus.C1000205
    
Extracting classification rules based on a cumulative probability distribution approach
Jr-shian Chen
Department of Computer Science and Information Management, Hungkuang University, Taiwan 433, Taichung
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Abstract  This paper deals with a reinforced cumulative probability distribution approach (CPDA) based method for extracting classification rules. The method includes two phases: (1) automatic generation of the membership function, and (2) use of the corresponding linguistic data to extract classification rules. The proposed method can determine suitable interval boundaries for any given dataset based on its own characteristics, and generate the fuzzy membership functions automatically. Experimental results show that the proposed method surpasses traditional methods in accuracy.

Key wordsCumulative probability distribution approach (CPDA)      Classification rule      C4.5     
Received: 18 June 2010      Published: 09 May 2011
CLC:  TP311  
Cite this article:

Jr-shian Chen. Extracting classification rules based on a cumulative probability distribution approach. Front. Inform. Technol. Electron. Eng., 2011, 12(5): 379-386.

URL:

http://www.zjujournals.com/xueshu/fitee/10.1631/jzus.C1000205     OR     http://www.zjujournals.com/xueshu/fitee/Y2011/V12/I5/379


Extracting classification rules based on a cumulative probability distribution approach

This paper deals with a reinforced cumulative probability distribution approach (CPDA) based method for extracting classification rules. The method includes two phases: (1) automatic generation of the membership function, and (2) use of the corresponding linguistic data to extract classification rules. The proposed method can determine suitable interval boundaries for any given dataset based on its own characteristics, and generate the fuzzy membership functions automatically. Experimental results show that the proposed method surpasses traditional methods in accuracy.

关键词: Cumulative probability distribution approach (CPDA),  Classification rule,  C4.5 
[1] Zhi-yong Yan, Cong-fu Xu, Yun-he Pan. Improving naive Bayes classifier by dividing its decision regions[J]. Front. Inform. Technol. Electron. Eng., 2011, 12(8): 647-657.