基于三支决策的不平衡数据过采样方法

doi:10.3969/j.issn.0372-2112.2018.01.019

电子学报 ›› 2018, Vol. 46 ›› Issue (1): 135-144.DOI: 10.3969/j.issn.0372-2112.2018.01.019

基于三支决策的不平衡数据过采样方法

胡峰, 王蕾, 周耀

计算智能重庆市重点实验室(重庆邮电大学), 重庆 400065

收稿日期:2016-05-10 修回日期:2016-10-31 出版日期:2018-01-25
- 作者简介:
- 胡峰,男,1978年7月出生,湖北天门人,教授、硕士生导师.2000年、2003年和2011年分别在重庆大学、武汉大学和西南交通大学获得理学学士、工学硕士和工学博士学位,现为重庆邮电大学教师.主要研究方向为数据挖掘、Rough集和粒计算等.E-mail:hufeng@cqupt.edu.cn;王蕾,男,1989年出生于山东德州,重庆邮电大学在读硕士研究生.主要研究方向为数据挖掘、三支决策、Rough集.
- 基金资助:
- 国家自然科学基金 (No.61309014，No.61379114，No.61472056）; 教育部人文社科规划 (No.15XJA630003）; 重庆市基础与前沿研究计划 (No.cstc2013jcyjA40063，No.cstc2014jcyjA40049）; 重庆市教委科学技术研究 (No.KJ1500416）

An Oversampling Method for Imbalance Data Based on Three-Way Decision Model

HU Feng, WANG Lei, ZHOU Yao

Chongqing Key Laboratory of Computational Intelligence(Chongqing University of Posts and Telecommunications), Chongqing 400065, China

Received:2016-05-10 Revised:2016-10-31 Online:2018-01-25 Published:2018-01-25
- Supported by:
- National Natural Science Foundation of China (No.61309014, No.61379114, No.61472056); Humanities and Social Science Program of Ministry of Education (No.15XJA630003); Chongqing Research Program of Basic and Frontier Technology (No.cstc2013jcyjA40063, No.cstc2014jcyjA40049); Science and Technology Research of Chongqing Municipal Education Commission (No.KJ1500416)

摘要/Abstract

摘要： 采样是解决不平衡数据分类问题的一个有效途径.文中结合三支决策理论，根据样本分布将样本划分成三个区域：正域、边界域和负域；在此基础上，分别对边界域和负域中的小类样本进行不同的过采样处理，提出了一种基于三支决策的不平衡数据过采样算法（TWD-IDOS算法）.实验结果表明，在C4.5、KNN和CART等分类器上，文中提出的算法能有效解决不平衡数据的二分类问题，在Recall、F-value、AUC等指标上优于文献中的过采样算法.

关键词: 三支决策, 邻域粗糙集, 边界采样, 不平衡数据, SMOTE

Abstract: Sampling is an effective way to solve the problem of unbalanced data classification. According to the distribution of samples, we employ the three-way decision model to divide the universe into three parts:positive region, boundary region and negative region. After that, we oversample the minority class samples in boundary region and negative region respectively. Then, a novel oversampling algorithm for imbalance data based on three-way decision model, namely TWD-IDOS, is developed. The experimental results show that the proposed method can effectively solve the two-class classification problems of imbalanced data and has a better performance in such measures (Recall, F-value, AUC) on C45, KNN and CART classifiers than other oversampling methods.

Key words: three-way decision, neighborhood rough set, boundary sampling, imbalanced data, SMOTE

中图分类号:

TP39

胡峰, 王蕾, 周耀. 基于三支决策的不平衡数据过采样方法[J]. 电子学报, 2018, 46(1): 135-144.

HU Feng, WANG Lei, ZHOU Yao . An Oversampling Method for Imbalance Data Based on Three-Way Decision Model[J]. Acta Electronica Sinica, 2018, 46(1): 135-144.

参考文献

[1] DRUMMOND C,et al.C4.5,class imbalance,and cost sensitivity:why under-sampling beats over-sampling[A].Proceedings of ICML Workshop on Learning from Im-Balanced Datasets Ⅱ[C].New York:ACM,2003.1-8.
[2] CHAWLA N V,BOWYER K W,et al.SMOTE:synthetic minority over-sampling technique[J].Journal of Artificial Intelligence Research,2002,(16):321-357.
[3] YEN S J,et al.Cluster-based under-sampling approaches for imbalanced data distributions[J].Expert Systems with Applications,2009,36(3):5718-5727.
[4] HAN H,WANG W Y,MAO B H.Borderline-SMOTE:anew over-sampling method in imbalanced data sets learning[A].Proceedings of International Conference on Intelligent Computing (ICIC)[C].Germany:Springer,2005.878-887.
[5] 杨智明,乔立岩,彭喜元.基于改进SMOTE的不平衡数据挖掘方法研究[J].电子学报,2007,35(12):22-26. YANG Zhiming,QIAO Liyan,PENG Xiyuan.Research on data ming method for imbalanced dataset based on improved SMOTE[J].Acta Electronica Sinica,2007,35(12):22-26.(in Chinese)
[6] RAMENTOL E,CABALLERO YAILé,BELLO R,et al.SMOTE-RSB*:a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory[J].Knowledge and Information Systems,2012,33(2):245-265.
[7] 曾志强,吴群,廖备水,等.一种基于核SMOTE的非平衡数据集分类方法[J].电子学报,2009,37(11):2489-2495. ZENG Zhiqiang,WU Qun,LIAO Beishui,et al.A classfication method for imbalance data set based on Kernel SMOTE[J].Acta Electronica Sinica,2009,37(11):2489-2495.(in Chinese)
[8] 翟云,王树鹏,马楠,等.基于单边选择链和样本分布密度融合机制的非平衡数据挖掘方法[J].电子学报,2014,42(7):1311-1319. ZHAI Yun,WANG Shupeng,MA Nan,et al.A data mining method for imbalanced datasets based on one-sided link and distribution density of instance[J].Acta Electronica Sinica,2014,42(7):1311-1319.(in Chinese)
[9] 王磊,黄河笑,吴兵,等.基于主题与三支决策的文本情感分析[J].计算机科学,2015,42(6):93-96. WANG Lei,HUANG Hexiao,WU Bing,et al.Emotion analysis of text based on topics and three-way decisions[J].Computer Science,2015,42(6):93-96.(in Chinese)
[10] LI H X,et al.Sequential three-way decision and granulation for cost-sensitive face recognition[J].Knowledge-Based Systems,2016,91(1):241-251.
[11] LIU D,LI T R,et al.Incorporating logistic regression to decision-theoretic rough sets for classifications[J].International Journal of Approximate Reasoning,2014,55(1):197-210.
[12] YU H,ZHANG C,WANG G Y.A tree-based incremental overlapping clustering method using the three-way decision theory[J].Knowledge-Based Systems,2016,91(1):189-203.
[13] LIU S L,LIU X W.A novel three-way decision basedon linguistic evaluation[A].Proceedings of 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)[C].Istanbul:IEEE,2015.1-7.
[14] LIU D,LIANG D C,et al.A novel three-way decision model based on incomplete information system[J].Knowledge-Based Systems,2016,91(1):32-45.
[15] CHEN Y M,ZENG Z Q,et al.Three-way decision reduction in neighborhood systems[J].Applied Soft Computing,2016,38(1):942-954.
[16] LIU D,LI T R,et al.A multiple-category classification approach with decision-theoretic rough sets[J].Fundamenta Informaticae,2012,115(2-3):173-188.
[17] ZHOU B.Multi-class decision-theoretic rough sets[J].International Journal of Approximate Reasoning,2014,55(1):211-224.
[18] LIN T Y.Neighborhood systems and approximation in relational databases and knowledge bases[A].Proceedings of the Fourth International Symposium on Methodologies of Intelligent Systems[C].Charlotte NC:Oak Ridge National Laboratory,1989.75-86.
[19] HU Q H,et al.Neighborhood classifiers[J].Expert Systems with Applications,2008,34(2):866-876.
[20] STANFILL C,WALTZ D.Toward memory-based reasoning[J].Communications of the ACM,1986,29(12):1213-1228.
[21] YAO Y Y.An outline of a theory of three-way decisions[A].Proceedings of Eighth International Conference of RSCTC[C].Germany:Springer,2012.1-17.
[22] 刘盾,李天瑞,苗夺谦,等.三支决策与粒计算[M].北京:科学出版社,2013.12-30. LIU Dun,LI Tianrui,MIAO Duoqian,et al.Three-Way Decision and Granular Computing[M].Beijing:Science Press,2013.12-30.(in Chinese)
[23] HU F,LI H.A novel boundary oversampling algorithm based on neighborhood rough set model:NRSBoundary-SMOTE[J/OL].Mathematical Problems in Engineering,2013,Article ID 694809,doi:10.1155/2013/694809.
[24] LAURIKKALA J.Improving identification of difficult smallclasses by balancing class distribution[A].Proceedings of Eighth Conference on Artificial Intelligence in Medicine in Europe (AIME)[C].Germany:Springer,2001.63-66.
[25] TOMEK I.An experiment with the edited nearest-neighbor rule[J].IEEE Transactions on Systems,Man,and Cybernetics,1976,6(6):448-452.
[26] LIU X Y,WU J,ZHOU Z H.Exploratory under-sampling for class-imbalance learning[J].IEEE Transactions on Systems,Man,and Cybernetics,Part B (Cybernetics),2009,39(2):539-550.
[27] Wikipedia Weka (machine learning)[CP/OL].http://en.wikipedia.org/wiki/Weka,2010.
[28] Learning and Mining from Data (LAMDA)[CP/OL].http://lamda.nju.edu.cn/CH.Data.ashx,2016-10-31.

基于三支决策的不平衡数据过采样方法

An Oversampling Method for Imbalance Data Based on Three-Way Decision Model

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