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 words: Cumulative probability distribution approach (CPDA), Classification rule, C4.5

Please provide your name, email address and a comment

Your Name: Affili: E-Mail Address:

Comment (Please comment in English):


Verification Code(click to change a pic):