期刊論文
| 學年 | 101 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2012-12-01 |
| 作品名稱 | Simplification of Support Vector Solutions Using Artificial Bee Colony Algorithm |
| 作品名稱（其他語言） | |
| 著者 | Tsai, Yih-Jia; Yeh, Jih-Pin |
| 單位 | 淡江大學資訊工程學系 |
| 出版者 | Singapore: World Scientific Publishing Co. Pte. Ltd. |
| 著錄名稱、卷期、頁數 | International Journal of Pattern Recognition and Artificial Intelligence 26(8), 1250020(14pages) |
| 摘要 | Support vector machines (SVMs) are a relatively recent machine learning technique. One of the SVM problems is that SVM is considerably slower in test phase caused by the large number of support vectors, which limits its practical use. To address this problem, we propose an artificial bee colony (ABC) algorithm to search for an optimal subset of the set of support vectors obtained through the training of the SVM, such that the original discriminant function is best approximated. Experimental results show that the proposed ABC algorithm outperforms some other compared methods in terms of the classification accuracy when the solution is reduced to the same size. |
| 關鍵字 | Artificial bee colony (ABC) algorithm;discriminant function;support vector machine (SVM);swarm intelligence (SI) |
| 語言 | en |
| ISSN | 0218-0014 |
| 期刊性質 | 國外 |
| 收錄於 | SCI EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | SGP |
| 公開徵稿 | |
| 出版型式 | 紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/78636 ) |