查詢結果分析
相關文獻
頁籤選單縮合
題名 | Generating Weighted Fuzzy Rules from Training Data for Dealing with the Iris Data Classification Problem= |
---|---|
作者 | Chen, Yung-chou; Wang, Li-hui; Chen, Shyi-ming; |
期刊 | International Journal of Applied Science and Engineering |
出版日期 | 20060400 |
卷期 | 4:1 民95.04 |
頁次 | 頁41-52 |
分類號 | 448.942 |
語文 | eng |
關鍵詞 | Fuzzy classification systems; Fuzzy sets; Iris data; Membership functions; Weighted fuzzy rules; |
英文摘要 | The most important task in the design of fuzzy classification systems is to find a set of fuzzy rules from training data to deal with a specific classification problem. In this paper, we present a new method to generate weighted fuzzy rules from training data to deal with the Iris data classification problem. First, we convert the training data to fuzzy rules, and then we merge those fuzzy rules in order to reduce the number of fuzzy rules. Then, we calculate the weight of each input variable appearing in the generated fuzzy rules by the relationships of input variables. The proposed weighted fuzzy rules generation method gets a higher average classification accuracy rate than the existing methods. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。