| 一种基于近邻元分析的文本分类算法 |
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| 引用本文： | 刘丛山,李祥宝,杨煜普.一种基于近邻元分析的文本分类算法[J].计算机工程,2012,38(15):139-141. |
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| 作者姓名： | 刘丛山 李祥宝 杨煜普 |
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| 作者单位： | 上海交通大学自动化系系统控制与信息处理教育部重点实验室,上海,200240 |
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| 基金项目： | 国家“863”计划基金资助项目“云制造服务平台关键技术” |
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| 摘 要： | 在近邻元分析(NCA)算法的基础上，提出K近邻元分析分类算法K-NCA。利用NCA算法完成对训练样本集的距离测度学习和降维，定义类偏斜因子，引入K近邻思想，得到测试样本的类条件概率估计，并通过该概率进行类别判定，实现文本分类器功能。实验结果表明，K-NCA算法的分类效果较好。
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| 关 键 词： | 近邻元分析 距离测度学习 降维 K近邻 文本分类 |
| 收稿时间： | 2011-09-29 |
Text Classification Algorithm Based on Neighborhood Component Analysis |
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| LIU Cong-shan
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LI Xiang-bao
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YANG Yu-pu.Text Classification Algorithm Based on Neighborhood Component Analysis[J].Computer Engineering,2012,38(15):139-141. |
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| Authors: | LIU Cong-shan LI Xiang-bao YANG Yu-pu |
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| Affiliation: | (Key Laboratory of System Control and Information Processing,Ministry of Education,Department of Automation,Shanghai Jiaotong University,Shanghai 200240,China) |
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| Abstract: | This paper proposes a novel algorithm named K-NCA based on Neighborhood Component Analysis(NCA).It uses NCA to learn a Mahalanobis distance measure and reduces the dimension of the input dataset.The algorithm defines a class imbalance factor and introduces K Nearest Neighbor(KNN) to compute the test sample’s class-conditional probability estimation.The sample’s class label is decided by this probability.A text classifier is designed to accomplish the algorithm.Experimental results show that K-NCA algorithm can improve the accuracy of text classification. |
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| Keywords: | Neighborhood Component Analysis(NCA) distance metric learning dimension reduction K Nearest Neighbor(KNN) text classification |
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