New filter method for feature selection based on graph

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (26): 186-188.

• 图形、图像、模式识别 • Previous Articles Next Articles

New filter method for feature selection based on graph

ZHANG Qi1，LIN Yuanyuan1，YU Guoxian2

1.Institute of Computer Architecture，South China University of Technology，Guangzhou 510006，China
2.College of Computer Science and Engineering，South China University of Technology，Guangzhou 510006，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-09-11 Published:2011-09-11

一种基于图的特征选择方法

张齐1，林媛媛1，余国先2

1.华南理工大学计算机系统结构研究所，广州 510006
2.华南理工大学计算机科学与工程学院，广州 510006

Abstract

Abstract: In many machine learning and data mining tasks，feature subset selection is an important step in data preprocessing.This paper presents a Graph Based Feature Selection（GBFS） algorithm，which is based on the graph，and prefers the features with local information preserving and global discriminative power.The experimental results validate its effectiveness in feature subset selection.

Key words: feature selection, graph based, local and global information

摘要： 在很多的机器学习和数据挖掘任务中，特征子集选择是重要的数据预处理步骤之一。提出一种基于图方法的无监督式特征选择方法（GBFS），构造一个以样本数据为顶点，数据间相似性作为边的图，再根据各特征的得分优先选择那些具有局部信息保持和全局区分能力的特征。实验结果表明，基于该方法选择的特征子集，在大多数情况下都能取得较好的分类效果。

关键词: 特征选择, 基于图的方法, 局部和全局信息

ZHANG Qi1，LIN Yuanyuan1，YU Guoxian2. New filter method for feature selection based on graph[J]. Computer Engineering and Applications, 2011, 47(26): 186-188.

张齐1，林媛媛1，余国先2. 一种基于图的特征选择方法[J]. 计算机工程与应用, 2011, 47(26): 186-188.

[1]	LI Li, JI Xinyuan, SONG Song. Prediction Model for Number of Software Defects in Loop [J]. Computer Engineering and Applications, 2021, 57(7): 158-163.
[2]	LI Jingxing, YANG Youlong. Feature Selection of Markov Blanket for High Dimensional Data [J]. Computer Engineering and Applications, 2021, 57(6): 58-66.
[3]	LIN Weixing, WANG Yujia, CHEN Wanfen, LIANG Haina. High-Dimensional Data Feature Selection Algorithm Based on Multifactor Particle Swarm Optimization [J]. Computer Engineering and Applications, 2021, 57(22): 199-207.
[4]	LI Longzhu, LIN Yaojin, LYU Yan, LU Shun, WANG Chenxi. Online Streaming Feature Selection Algorithm Using Neighborhood Information Interaction [J]. Computer Engineering and Applications, 2021, 57(21): 102-108.
[5]	CHEN Qianru, LI Yali, XU Kequan, LIU Yilong, WANG Shuqin. WKNN Feature Selection Method Based on Self-Tuning Adaptive Genetic Algorithm [J]. Computer Engineering and Applications, 2021, 57(20): 164-171.
[6]	WU Weijie, ZHANG Jingxiang. Random Forest Feature Selection Algorithm Based on Categorization Information and Application [J]. Computer Engineering and Applications, 2021, 57(17): 147-156.
[7]	QIU Yunfei, GAO Huacong. Hybrid Filter and Improved Adaptive GA for Feature Selection [J]. Computer Engineering and Applications, 2021, 57(11): 95-102.
[8]	HUO Lin, LU Yinli. Improved Particle Swarm Optimization for Android Malware Detection [J]. Computer Engineering and Applications, 2020, 56(7): 96-101.
[9]	LIAO Wenxiong, ZENG Bi, LIANG Tiankai, XU Yayun, ZHAO Junfeng. Personal Credit Risk Assessment Method for High-Dimensional Data [J]. Computer Engineering and Applications, 2020, 56(4): 219-224.
[10]	PENG Ming, ZHANG Haipeng. Unsupervised Feature Selection via Schatten-p Norm and Feature Self-Representation [J]. Computer Engineering and Applications, 2020, 56(23): 45-52.
[11]	LIU Feng, Godfred Kim Mensah, LI Xinyun, LIU Hongli, LI Yao, GUO Hao. Abnormal Topological Analysis and Classification Research of Uncertain Brain Networks [J]. Computer Engineering and Applications, 2020, 56(2): 127-132.
[12]	YUE Peng, HOU Lingyan, YANG Dali, TONG Qiang. XLC-Stacking Method for Disease Diagnosis Based on XGBoost Feature Selection [J]. Computer Engineering and Applications, 2020, 56(17): 136-141.
[13]	HUANG Xin, MO Haimiao, ZHAO Zhigang, ZENG Min. Research on Discrete Enhanced Fireworks Algorithm and [kNN] in Feature Selection [J]. Computer Engineering and Applications, 2020, 56(16): 112-117.
[14]	ZHOU Wanying, MA Yingcang, XU Qiuxia, ZHENG Yi. Unsupervised Feature Selection Algorithm Based on Maximum Entropy and [l2,0] Norm Constraints [J]. Computer Engineering and Applications, 2020, 56(11): 51-59.
[15]	CHEN Jia, LIU Dongxue, WU Dashuo. Stock Index Forecasting Method Based on Feature Selection and LSTM Model [J]. Computer Engineering and Applications, 2019, 55(6): 108-112.

New filter method for feature selection based on graph

一种基于图的特征选择方法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics