Improved Feature Selection Method Based on CHI for Text Categorization

SONG Cheng-xiang; CHEN Xiu-hong; NIU Qiang

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Improved Feature Selection Method Based on CHI for Text Categorization

更新时间：2026-09-04

- Improved Feature Selection Method Based on CHI for Text Categorization
- Vol. 35, Issue 9, Pages: 74-78(2018)
- 作者机构：
  
  江南大学数字媒体学院,江苏,无锡,214122
- 作者简介：
- 基金信息：
- DOI：
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- Published：2018
- 稿件说明：
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宋呈祥, 陈秀宏, 牛强. 文本分类中基于CHI改进的特征选择方法[J]. 微电子学与计算机, 2018, 35(9): 74-78.

SONG Cheng-xiang, CHEN Xiu-hong, NIU Qiang. Improved Feature Selection Method Based on CHI for Text Categorization[J]. 2018, 35(9): 74-78.
宋呈祥, 陈秀宏, 牛强. 文本分类中基于CHI改进的特征选择方法[J]. 微电子学与计算机, 2018, 35(9): 74-78. DOI：

SONG Cheng-xiang, CHEN Xiu-hong, NIU Qiang. Improved Feature Selection Method Based on CHI for Text Categorization[J]. 2018, 35(9): 74-78. DOI：

摘要

针对传统卡方统计量(CHI)方法在全局范围内做特征选择时忽略词的频度、词的分布等问题

提出了一种改进的文本特征选择方法.该方法通过定义特征词频度分布相关性系数

选择局部出现的强相关性特征

同时考虑特征词类间分布差异性来提升不均衡数据集的分类指标.结果表明

改进的方法不仅在分类效果上有明显的提高

而且性能更加稳定.

Abstract

Because the traditional Chi-square methodchooses the feature in the global scope and ignores theinformationof word frequency and distribution

this paper proposes animproved feature selection method. The method selects anumber of strong featureswith thedefined feature distributioncoefficient

andtakes into account featuredistribution thatimproves theperformances of Chi-square method in theunbalanced dataset.The results of the experimentshow that the improved algorithmnot only shows a significant improvement in classification efficiency

but also has more stable performance.

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references

Jin C, Ma T, Hou R, et al. Chi-square Statistics Feature Selection Based on Term Frequency and Distribution for Text Categorization[J]. Iete Journal of Research, 2015, 61(4):351-362. DOI: 351

邱云飞, 王威, 刘大有, 等.基于方差的CHI特征选择方法[J].计算机应用研究, 2012, 29(4):1304-1306. DOI: 1304

Junejo K N, Karim A, Hassan M T, et al. Terms-based discriminative information space for robust text classification[J]. Information Sciences, 2016, 372(c):518-538. DOI: 518

谢娜娜, 房斌, 吴磊.不均衡数据集上文本分类方法研究[J].计算机工程与应用, 2013, 49(20):118-121. DOI: 118

周爱武, 马那那, 刘慧婷.基于卡方统计的情感文本分类[J].微电子学与计算机, 2017, 34(8):57-61. DOI: 57

叶敏, 汤世平, 牛振东.一种基于多特征因子改进的中文文本分类算法[J].中文信息学报, 2017, 31(4):132-137. DOI: 132

Yang Y, Pedersen JO. A Comparative Study on Feature Selection in Text Categorization[C]// Fourteenth International Conference on Machine Learning. Morgan Kaufmann Publishers Inc. 1997: 412-420.

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