A Feature Selection Method Based on Improved Category Distribution

徐红国; 王素格

您当前的位置：

首页 >

文章列表页 >

A Feature Selection Method Based on Improved Category Distribution

更新时间：2026-09-14

- A Feature Selection Method Based on Improved Category Distribution
- 基于改进的类别分布特征选择方法
- Vol. 32, Issue 2, Pages: 139-142(2011)
- 作者机构：
  
  山西大学数学科学学院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2011
- 稿件说明：
移动端阅览
徐红国, 王素格. A Feature Selection Method Based on Improved Category Distribution[J]. 2011, 32(2): 139-142.
DOI：

徐红国, 王素格. A Feature Selection Method Based on Improved Category Distribution[J]. 2011, 32(2): 139-142. DOI：

摘要

随着网络上非平衡数据的大量涌现

使得对非平衡数据分类的研究成为一个新的研究热点.根据特征在类别中的分布特点

提出了基于类间、类内分布的方法.该方法不但充分考虑了稀有类别信息对特征选择的影响

使得构造的类别分布函数能够相当好地反映稀有特征的信息

而且能够选出对非平衡数据分类贡献大的特征.实验结果表明:此方法的MacroF1和MicroF1皆优于基于类别分布的特性选择(Category Distribution-Based Feature Selection

CDFS)和类别信息的方法.

Abstract

With the unbalanced data set emerging in large numbers on the internet

the research on the unbalanced data classification becomes a new hotspot.According to the feature's distribution characteristics in the classification

a new feature selection method based on inter-class and between-classes distributions was proposed.The proposed method not only takes full account of the rare category of information's impact on the feature selection

making the constructed distribution function well reflect the characteristics of rare information

but also selects the features of significant contribution for unbalanced data classification.The experimental results show that both MacroF1 and MicroF1 of the proposed method have advantages over Category DistributionBased Feature Selection(CDFS) method and the class information method.

关键词

Keywords

references

徐燕,李锦涛,王斌,等.不均衡数据集上文本分类的特征选择研究[J].计算机研究与发展,2007,44(Suppl):58-62.Xu Yan,Li Jintao,Wang Bin,et al.A study of feature selection for text categorization on imbalanced data[J].Journal of Computer Research and Development,2007,44(Suppl):58-62.(in Chinese)

Zheng Z,Wu X,Srihari R.Feature selection for text categorization on imbalanced data[C].Proc of ACM SIGKDDExplorations Newsletter.New York:ACM,2004:80-89.

谢纪刚,裘正定.非平衡数据集Fisher线形判别模型[J].北京交通大学学报,2006(10):15-18.Xie Jigang,Qiu Zhengding.Fisher linear discriminant model with class imbalance[J].Journal of Beijing JIaotongUniversity,2006(10):15-18.(in Chinese)

Yan J,Liu N,Zhang B,et al.OCFS:Optimal orthogonal centroid feature selection for text categorization[C].Procof SIGIR’05.New York:ACM,2005:122-129.

余俊英,王明文.文本分类中的类别信息特征选择方法[J].山东大学学报(自然科学版),2006,41(3):1671-9352.Yu Junying,Wang Mingwen.Class information feature selection method for text classification[J].Journal ofShandong University(Natural Science Edition),2006,41(3):1671-9352.(in Chinese)

婧红芳,王斌,杨雅辉,等.基于类别分布的特征选择框架[J].计算机研究与发展,2009,46(9):1586-1593.Jing Hongfang,Wang Bin,Yang Yahui,et al.Category distribution-based feature selection framework[J].Journalof Computer Research and Development,2009,46(9):1586-1593.(in Chinese)

边肇祺,张学工.模式识别[M].北京:清华大学出版社,2001.

Views

135

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Chinese Depression Text Classification Based on Domain Emotion Dictionary and Word Feature Fusion

Data Mining and Its Applicatin in Super Market

Adaptive DFT Channel Estimation Algorithm Based on Joint Delay and SNR Estimation in OFDM System

Study on the Ultrasonic Adsorption of Cr（Ⅵ） in Water by Tea Biochar Magnetic Materials

《中北大学学报(自然科学版》》征稿简则

Related Author

刘豪

卓广平

乔俊福

张光华

田容

陈立潮

张晋

Related Institution

太原师范学院计算机系

太原工业学院自动化系

华北工学院计算机科学与技术系

⁰