關鍵字查詢 | 類別:期刊論文 | | 關鍵字:Simplification of Support Vector Solutions Using Artificial Bee Colony Algorithm

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序號 學年期 教師動態
1 101/1 資工系 蔡憶佳 副教授 期刊論文 發佈 Simplification of Support Vector Solutions Using Artificial Bee Colony Algorithm , [101-1] :Simplification of Support Vector Solutions Using Artificial Bee Colony Algorithm期刊論文Simplification of Support Vector Solutions Using Artificial Bee Colony AlgorithmTsai, Yih-Jia; Yeh, Jih-Pin淡江大學資訊工程學系Artificial bee colony (ABC) algorithm;discriminant function;support vector machine (SVM);swarm intelligence (SI)Singapore: World Scientific Publishing Co. Pte. Ltd.International Journal of Pattern Recognition and Artificial Intelligence 26(8), 1250020(14pages)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 algorith
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