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標題: A Modified Lion's Algorithm for Feature Selection of Support Vector Machines
作者: 黃齡德
Ling-De Huang
關鍵字: feature selection;lion algorithm;support vector machine;特徵選取;獅子演算法;支援向量機
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Feature selection is an effective method on the solving of classification problem. Through reduce unnecessary features, feature selection can improve accuracy of classification and reduce the training time of classifiers. Besides, the bio-inspired algorithms are usually used to search the optimal feature subset for a classifier. Lion's algorithm is the newly developed bio-inspired algorithm with social behavior of lions. This study illustrates a modified version of lion's algorithm to improve the search efficiency. By using the dataset of UCI machine learning database, the proposed method was compared with the basic lion's algorithms. Experimental results demonstrated that the performance of the proposed method was superior to that of the basic lion's algorithms.


在本研究中,我們提出了改良的獅子演算法,於原本獅子演算法領土防禦的過程中增加了全鄰域搜索,進而提升獅子演算法的搜尋效率。並將改良的獅子演算法整合支援向量機應用於特徵選取上,針對改良的獅子演算法提出最佳參數組合。實驗中使用 UCI 的資料集來進行演算法的效能測試,實驗的結果顯示改良後的獅子演算法於大多數的資料集的分類正確率優於原本的獅子演算法。
其他識別: U0005-0606201510043800
Rights: 不同意授權瀏覽/列印電子全文服務
Appears in Collections:資訊管理學系

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