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文本分类中特征提取方法的比较与分析 被引量：8

Comparison and Analysis of Feature Extraction Methods for Text Categorization
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摘要 研究了在文本分类中,各种特征提取方法对分类效果的影响,比较了特征提取方法交叉熵(CE)、信息增益(IG)、互信息(MI)、及χ2对文本分类器性能的影响,分析了这几种特征提取方法对SVM和KNN分类器性能的影响。 Studies feature extraction in text categorization, compares cross entropy （CE）, information gain（IG）, mutual information（MI）, X^2-test（CHI） and class selection these four method, analyzes the influence of performance of these feature extraction methods on SVM and KNN these two classifiers.
作者 屈军 林旭
机构地区 广东省台山电视大学 广东省工业贸易学校
出处 《现代计算机》 2007年第4期10-13,共4页 Modern Computer
关键词 文本自动分类 KNN SVM 特征提取 Text Categorization KNN SVM Feature Extraction
分类号 TP391.1 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献11

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二级参考文献14

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共引文献125

同被引文献59

引证文献8

二级引证文献34

现代计算机
2007年 第4期

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