| 一种基于模糊理论的KNN文本分类算法 |
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| 引用本文： | 曾洪波,杨天奇,邱韬奋.一种基于模糊理论的KNN文本分类算法[J].微计算机应用,2011,32(2). |
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| 作者姓名： | 曾洪波 杨天奇 邱韬奋 |
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| 作者单位： | 暨南大学信息科学技术学院,广州,510632 |
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| 摘 要： | 传统的KNN文本分类算法在处理不均匀数据时,尤其是小型数据,容易受到边缘数据的干扰,导致分类效果明显下降.对此,本文提出一种基于模糊理论的KNN文本分类算法,该算法根据模糊理论的思想计算样本的隶属度函数,更合理地处理训练样本权值.实验表明,基于模糊理论的KNN算法能有效的弱化这些干扰,并在分类准确度上也有一定的提高.
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| 关 键 词： | 文本分类 KNN 模糊理论 隶属度函数 |
A KNN Text Classification Algorithm Based on Fuzzy Theory |
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| ZENG Hongbo,YANG Tianqi,QIU Taofen.A KNN Text Classification Algorithm Based on Fuzzy Theory[J].Microcomputer Applications,2011,32(2). |
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| Authors: | ZENG Hongbo YANG Tianqi QIU Taofen |
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| Affiliation: | ZENG Hongbo,YANG Tianqi,QIU Taofen(College of Information Science and Technology,Jinan University,Guangzhou,510632,China) |
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| Abstract: | When the traditional KNN text categorization algorithm handles the non-uniform data,especially for the small data set,it is easy to be interfered by the edge of the data set,and then results in the obviously decrease of classification efficiency.In this regard,this paper presents a text classification algorithm based on fuzzy theory,this algorithm based on the membershi Pfunction of the thinking calculation samples of the fuzzy theory,the training samples weight will be handled reasonably.Experiments show t... |
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| Keywords: | text categorization KNN fuzzy theory membershi Pfunction |
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