| 基于微粒群优化的快速K-近邻分类算法 |
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| 引用本文： | 林令娟,刘希玉.基于微粒群优化的快速K-近邻分类算法[J].山东科学,2009,22(1):13-16. |
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| 作者姓名： | 林令娟 刘希玉 |
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| 作者单位： | 1. 山东师范大学信息科学与工程学院,山东,济南,250014
2. 山东师范大学管理与经济学院,山东,济南,250014 |
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| 基金项目： | 国家自然科学基金，山东省自然科学基金重点项目 |
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| 摘 要： | 随着全球信息化的出现,手工分类索引已经不适用于大规模信息的处理,自动分类的研究得到迅速发展。K-近邻法是具有一定效率的自动分类算法。本文将其与智能优化技术结合,用于基于机器学习的文本分类过程中。实验结果表明,对于庞大的文档集合分类,该算法提高了分类的速度和精度。
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| 关 键 词： | 微粒群优化(PSO) K-近邻分类算法 特征向量 |
A Particle Swarm Optimization Based Rapid K-Nearest Neighbor Classification Algorithm |
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| LIN Ling-juan,LIU Xi-yu.A Particle Swarm Optimization Based Rapid K-Nearest Neighbor Classification Algorithm[J].Shandong Science,2009,22(1):13-16. |
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| Authors: | LIN Ling-juan LIU Xi-yu |
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| Institution: | LIN Ling-juan, LIU Xi-yu( 1. School of Information Science and Engineering, Shandong Normal Uiversity, Jinan 250014, China ; 2. School of Management and Economies, Shandong Normal Uiversity, Jinan 250014, China) |
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| Abstract: | Manual sorting index has not been applicable to large-scale information processing,and the research on automatic sorting index vigorously developed with the emergence of global information.K-nearest neighbor algorithm is an automatic sorting index approach with a certain efficiency,which is combined with intelligent optimization technology and is applied to machine learning based text sorting process.The results show that the algorithm improves the sorting speed and accuracy for the sorting of huge documents set. |
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| Keywords: | particle swarm optimization(PSO) K-nearest neighbor classification algorithm eigenvector |
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