會議論文
| 學年 | 88 |
|---|---|
| 學期 | 2 |
| 發表日期 | 2000-05-07 |
| 作品名稱 | K-means-based fuzzy classifier design |
| 作品名稱（其他語言） | |
| 著者 | 翁慶昌; Wong, Ching-chang; Chen, Chia-chong; Yeh, Shih-liang |
| 作品所屬單位 | 淡江大學電機工程學系 |
| 出版者 | Institute of Electrical and Electronics Engineers (IEEE) |
| 會議名稱 | Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on |
| 會議地點 | San Antonio, TX, USA |
| 摘要 | In this paper, a method based on the K-means algorithm is proposed to efficiently design a fuzzy classifier so that the training patterns can be correctly classified by the proposed approach. In this method, the K-means algorithm is first used to partition the training data for each class into several clusters, and the cluster center and the radius for each cluster are calculated. Then, a fuzzy system design method that uses a fuzzy rule to represent a cluster is proposed such that a fuzzy classifier can be efficiently constructed to correctly classify the training data. The proposed method has the following features: 1) it does not need prior parameter definition; 2) it only needs a short training time; and 3) it is simple. Finally, two examples are used to illustrate and examine the proposed method for the fuzzy classifier design |
| 關鍵字 | |
| 語言 | en |
| 收錄於 | |
| 會議性質 | 國際 |
| 校內研討會地點 | |
| 研討會時間 | 20000507~20000507 |
| 通訊作者 | |
| 國別 | USA |
| 公開徵稿 | Y |
| 出版型式 | 紙本 |
| 出處 | Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on (Volume:1 ), pp.48-52 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/38703 ) |