Generating fuzzy rules from training instances for fuzzy classification systems

作者：Chen Shyi Ming^*; Tsai Fu Ming

来源：Expert Systems with Applications, 2008, 35(3): 611-621.

DOI：10.1016/j.eswa.2007.07.013

• fuzzy rules
• fuzzy sets
• fuzzy classification systems
• iris data
• membership functions

In recent years, many methods have been proposed to generate fuzzy rules from training instances for handling the Iris data classification problem. In this paper, we present a new method to generate fuzzy rules from training instances for dealing with the Iris data classification problem based on the attribute threshold value alpha, the classification threshold value beta and the level threshold value gamma, where alpha is an element of [0, 1], beta is an element of [0, 1] and gamma is an element of [0, 1]. The proposed method gets a higher average classification accuracy rate than the existing methods.

• 出版日期2008-10