Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/92946
標題: A Modified Lion's Algorithm for Feature Selection of Support Vector Machines
改良式獅子演算法於支援向量機之特徵選取應用
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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摘要: 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.
在進行分類問題演算的過程中,為了最佳化分類正確率,特徵選取是一個相當基本且重要的課題。透過特徵選取的方式,能有效減少不相關、雜訊、或重複性的資料,藉此改善分類效能。近年來常透過仿生演算法來進行求解,獅子演算法是基於獅子社會行為提出的仿生演算法,主要以領土防禦和領土爭奪來模擬獅子族群的兩大行為來達到解決最佳化問題的目的。 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。
URI: http://hdl.handle.net/11455/92946
其他識別: U0005-0606201510043800
文章公開時間: 10000-01-01
Appears in Collections:資訊管理學系

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