[1]YE Zhi-fei,WEN Yi-min,LU Bao-liang.A survey of imbalanced pattern classification problems[J].CAAI Transactions on Intelligent Systems,2009,4(2):148-156.
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A survey of imbalanced pattern classification problems

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 2 Page number: 148-156 Column: 综述 Public date: 2009-04-25
Title:
A survey of imbalanced pattern classification problems
Author(s):
YE Zhi-fei1; WEN Yi-min 2; LU Bao-liang 1; 3
1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;
2.Department of Information Engineering，Hunan Industry Polytechnic, Changsha 410208, China；
3.MOEMicrosoft Key Lab. for Intelligent Computing and Intelligent Systems, Shanghai Jiao Tong University, Shanghai 200240, China
Keywords:
machine learning;  imbalanced pattern classification;  resampling;  cost sensitive learning;  task decomposition;  classifier ensemble;  evaluation matrices
CLC:
TP181
DOI:
-
Abstract:
Imbalanced data sets have always been regarded as presenting significant difficulties when applying machine learning methods to realworld pattern classification problems. Although various approaches have been proposed during the past decade, limitations are imposed by many realworld imbalanced data sets, and as a result, a lot of further research is currently being done. In this paper, we provide an uptodate survey of research on imbalanced pattern classification problems. We first took a deep look into the problems that imbalanced data sets bring, and then we introduced different kinds of solutions in detail, with their representative approaches. Finally, using three real imbalanced data sets, we compared the performance of some typical methods including resampling, cost sensitive learning, training set partitions, and the performance of classifier ensembles. In addition, topics such as evaluation indexes and future areas of research were also discussed. 
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Last Update: 2009-05-04

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