Generating fuzzy rules from training instances for fuzzy classification systems
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 ?, the classification threshold value ? and the level threshold value ?, where ??[0,1], ??[0,1] and ??[0,1]. The proposed method gets a higher average classification accuracy rate than the existing methods.
fuzzy rules fuzzy classification systems iris data fuzzy sets membership functions