Extracting classification rules based on a cumulative probability distribution approach

作者：Chen Jr shian^*

来源：Journal of Zhejiang University-Science C(Computers and Electronics), 2011, 12(5): 379-386.

DOI：10.1631/jzus.C1000205

• Cumulative probability distribution approach (CPDA)
• Classification rule
• C4.5

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.

• 出版日期2011-5