關鍵字查詢 | 類別:期刊論文 | | 關鍵字:A new particle swarm feature selection method for classification

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序號 學年期 教師動態
1 102/2 企管系 陳昆皇 助理教授 期刊論文 發佈 A new particle swarm feature selection method for classification , [102-2] :A new particle swarm feature selection method for classification期刊論文A new particle swarm feature selection method for classificationK.-H. Chen; L.-F. Chen; C.-T. SuFeature selection;Particle swarm optimization;Regression;Genetic algorithms;Sequential search algorithmsJournal of Intelligent Information Systems 42(3), pp.507-530Searching for an optimal feature subset from a high-dimensional feature space is an NP-complete problem; hence, traditional optimization algorithms are inefficient when solving large-scale feature selection problems. Therefore, meta-heuristic algorithms are extensively adopted to solve such problems efficiently. This study proposes a regression-based particle swarm optimization for feature selection problem. The proposed algorithm can increase population diversity and avoid local optimal trapping by improving the jump ability of flying particles. The data sets collected from UCI machine learning databases are used to evaluate the effectiveness of the proposed appr
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