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李睿峰等:基于空间近邻关系的非平衡数据重采样算法 869· (高明哲,许爱强,许晴.SL-SMOTE和CS-RVM结合的电子设备 [19]Zhao Z X,Wang G L,Li X D.An improved SVM based under- 故障检测方法.计算机工程与应用,2019,55(4):185) sampling method for classifying imbalanced data.Acta Sci Nat [7]Feng H W,Yao B,Gao Y,et al.Imbalanced data processing Uniy Sunvatseni,2012,51(6):10 algorithm based on boundary mixed sampling.Control Decis, (赵自翔,王广亮,李晓东.基于支持向量机的不平衡数据分类 2017,32(10:1831 的改进欠采样方法.中山大学学报(自然科学版),2012,51(6): (冯宏伟,姚博,高原,等.基于边界混合采样的非均衡数据处理 10) 算法.控制与决策,2017,32(10):1831) [20]Chawla N V,Bowyer K W,Hall L O,et al.SMOTE:Synthetic [8]Gao M,Hong X,Chen S,et al.A combined SMOTE and PSO minority over-sampling technique.JArtif /ntell Res,2002,16:321 based RBF classifier for two-class imbalanced problems [21]Liu Y X.Liu S M.Liu T,et al.New oversampling algorithm Neurocomputing,2011,74(17):3456 DB_SMOTE.Comput Eng Appl,2014,50(6):92 [9]Gu P.Ouyang Y Y.Classification research for unbalanced data (刘余霞,刘三民,刘涛,等.一种新的过采样算法DB SMOTE based on mixed-sampling.App/Res Comput,2015,32(2):379 计算机工程与应用,2014,50(6):92) (古平,欧阳源遊.基于混合采样的非平衡数据集分类研究.计 [22]Gu Q,Yuan L,Ning B,et al.A novel classification algorithm for 算机应用研究,2015,32(2):379) imbalanced datasets based on hybrid resampling strategy.Compu [10]Yu H L,Yang X B.Zheng S,et al.Active learning from Eng Sci,2012,34(10):128 imbalanced data:A solution of online weighted extreme learning (谷琼,袁磊,宁彬,等.一种基于混合重取样策略的非均衡数据 machine.IEEE Trans Neural Networks Learn Syst,2019,30(4): 集分类算法.计算机工程与科学,2012,34(10):128) 1088 [23]Tao X M,Hao S Y,Zhang D X,et al.Support vector machine for [11]Cai YY,Song X D.New fuzzy SVM model used in imbalanced unbalanced data based on sample properties under-sampling datasets.J Xidian Univ Nat Sci,2015,42(5):120 approaches.Control Decis,2013,28(7):978 (蔡艳艳,宋晓东.针对非平衡数据分类的新型模糊SVM模型 (陶新民,郝思媛,张冬雪,等.基于样本特性欠取样的不均衡支 西安电子科技大学学报(自然科学版),2015,42(5):120) 持向量机.控制与决策,2013,28(7):978) [12]Wang C Y,Su H Y,Qu Y,et al.Imbalanced data sets [24]Bunkhumpompat C.Sinapiromsaran K,Lursinsap C.Safe-level- classification method based on over-sampling technique.Comput SMOTE:Safe-level-synthetic minority over-sampling technique Eg4ppl,2011,47(1):139 for handling the class imbalanced problem /Proceedings of (王春玉,苏宏业,渠瑜,等.一种基于过抽样技术的非平衡数据 Advances in Knowledge Discovery and Data Mining Conference. 集分类方法.计算机工程与应用,2011,47(1):139) [13]Zhang Y F,Guo H P,Zhi W M,et al.An ensemble pruning Bangkok,2009:475 [25]Huang G B,Zhou H M,Ding X J,et al.Extreme learning machine method for imbalanced data classification.Compur Eng,2014, 40(6):157 for regression and multiclass classification.IEEE Trans Syst Man (张银蜂,郭华平,职为梅,等.一种面向不平衡数据分类的组合 Cybern Part B Cybern,2012,42(2):513 剪枝方法.计算机工程,2014.40(6):157) [26]Gautam C,Tiwari A,Leng Q.On the construction of extreme [14]Vong C M,Ip W F,Wong P K,et al.Predicting minority class for learning machine for online and offline one-class classification-an suspended particulate matters level by extreme leaming machine. expanded toolbox.Neurocompuring,2017,261:126 Neurocomputing,2014,128:136 [27]Zhu M,Liu Q,Liu X,et al.Fault detection method for avionics [15]Zhai Y,Yang B R,Wang S P,et al.Under-sampling method based based on LMK and OC-ELM.Syst Eng Electron,2020,42(6): on cooperative co-evolutionary mechanism.J Univ Sci Technol 1424 Beijing,2011,33(12):1550 (朱敏,刘奇,刘星,等.基于LMK和OC-ELM的航空电子部件故 (翟云,杨炳儒,王树鹏,等.基于协同进化机制的欠采样方法 障检测方法.系统工程与电子技术,2020,42(6):1424) 北京科技大学学报,2011,33(12):1550) [28]Xue L X,Qiu B Z.Boundary points detection algorithm based on [16]Yang Y,Liu F,Jin Z Y,et al.Aliasing artefact suppression in coefficient of variation.Pattern Recognit Artif Intell,2009,22(5): compressed sensing MRI for random phase-encode undersampling 799 IEEE Trans Bio-Med Eng,2015,62(9):2215 (薛丽香,邱保志.基于变异系数的边界点检测算法.模式识别 [17]Jia C Z.Zuo Y.S-SulfPred:A sensitive predictor to capture S- 与人工智能,2009,22(5):799) sulfenylation sites based on a resampling one-sided selection [29]Zhang Z,Duan Z M,Long Y.Fault detection in switched current undersampling-synthetic minority oversampling technique. circuits based on preferred wavelet packet.Chin J Eng,2017, Theoret Biol,2017,422:84 39(7大:1101 [18]Wilson DL.Asymptotic properties of nearest neighbor rules using (张镇,段哲民,龙英.基于小波包的开关电流电路故障诊断.工 edited data.IEEE Trans Syst Man Cybern.2007.SMC-2(3):408 程科学学报,2017,39(7):1101)(高明哲, 许爱强, 许晴. SL-SMOTE和CS-RVM结合的电子设备 故障检测方法. 计算机工程与应用, 2019, 55(4):185) Feng H W, Yao B, Gao Y, et al. Imbalanced data processing algorithm based on boundary mixed sampling. Control Decis, 2017, 32(10): 1831 (冯宏伟, 姚博, 高原, 等. 基于边界混合采样的非均衡数据处理 算法. 控制与决策, 2017, 32(10):1831) [7] Gao M, Hong X, Chen S, et al. A combined SMOTE and PSO based RBF classifier for two-class imbalanced problems. Neurocomputing, 2011, 74(17): 3456 [8] Gu P, Ouyang Y Y. Classification research for unbalanced data based on mixed-sampling. Appl Res Comput, 2015, 32(2): 379 (古平, 欧阳源遊. 基于混合采样的非平衡数据集分类研究. 计 算机应用研究, 2015, 32(2):379) [9] Yu H L, Yang X B, Zheng S, et al. Active learning from imbalanced data: A solution of online weighted extreme learning machine. IEEE Trans Neural Networks Learn Syst, 2019, 30(4): 1088 [10] Cai Y Y, Song X D. New fuzzy SVM model used in imbalanced datasets. J Xidian Univ Nat Sci, 2015, 42(5): 120 (蔡艳艳, 宋晓东. 针对非平衡数据分类的新型模糊SVM模型. 西安电子科技大学学报(自然科学版), 2015, 42(5):120) [11] Wang C Y, Su H Y, Qu Y, et al. Imbalanced data sets classification method based on over-sampling technique. Comput Eng Appl, 2011, 47(1): 139 (王春玉, 苏宏业, 渠瑜, 等. 一种基于过抽样技术的非平衡数据 集分类方法. 计算机工程与应用, 2011, 47(1):139) [12] Zhang Y F, Guo H P, Zhi W M, et al. An ensemble pruning method for imbalanced data classification. Comput Eng, 2014, 40(6): 157 (张银峰, 郭华平, 职为梅, 等. 一种面向不平衡数据分类的组合 剪枝方法. 计算机工程, 2014, 40(6):157) [13] Vong C M, Ip W F, Wong P K, et al. Predicting minority class for suspended particulate matters level by extreme learning machine. Neurocomputing, 2014, 128: 136 [14] Zhai Y, Yang B R, Wang S P, et al. Under-sampling method based on cooperative co-evolutionary mechanism. J Univ Sci Technol Beijing, 2011, 33(12): 1550 (翟云, 杨炳儒, 王树鹏, 等. 基于协同进化机制的欠采样方法. 北京科技大学学报, 2011, 33(12):1550) [15] Yang Y, Liu F, Jin Z Y, et al. Aliasing artefact suppression in compressed sensing MRI for random phase-encode undersampling. IEEE Trans Bio-Med Eng, 2015, 62(9): 2215 [16] Jia C Z, Zuo Y. 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Comput Eng Sci, 2012, 34(10): 128 (谷琼, 袁磊, 宁彬, 等. 一种基于混合重取样策略的非均衡数据 集分类算法. 计算机工程与科学, 2012, 34(10):128) [22] Tao X M, Hao S Y, Zhang D X, et al. Support vector machine for unbalanced data based on sample properties under-sampling approaches. Control Decis, 2013, 28(7): 978 (陶新民, 郝思媛, 张冬雪, 等. 基于样本特性欠取样的不均衡支 持向量机. 控制与决策, 2013, 28(7):978) [23] Bunkhumpornpat C, Sinapiromsaran K, Lursinsap C. Safe-level￾SMOTE: Safe-level-synthetic minority over-sampling technique for handling the class imbalanced problem // Proceedings of Advances in Knowledge Discovery and Data Mining Conference. Bangkok, 2009: 475 [24] Huang G B, Zhou H M, Ding X J, et al. Extreme learning machine for regression and multiclass classification. IEEE Trans Syst Man Cybern Part B Cybern, 2012, 42(2): 513 [25] Gautam C, Tiwari A, Leng Q. On the construction of extreme learning machine for online and offline one-class classification-an expanded toolbox. Neurocomputing, 2017, 261: 126 [26] Zhu M, Liu Q, Liu X, et al. Fault detection method for avionics based on LMK and OC-ELM. Syst Eng Electron, 2020, 42(6): 1424 (朱敏, 刘奇, 刘星, 等. 基于LMK和OC-ELM的航空电子部件故 障检测方法. 系统工程与电子技术, 2020, 42(6):1424) [27] Xue L X, Qiu B Z. Boundary points detection algorithm based on coefficient of variation. Pattern Recognit Artif Intell, 2009, 22(5): 799 (薛丽香, 邱保志. 基于变异系数的边界点检测算法. 模式识别 与人工智能, 2009, 22(5):799) [28] Zhang Z, Duan Z M, Long Y. Fault detection in switched current circuits based on preferred wavelet packet. Chin J Eng, 2017, 39(7): 1101 (张镇, 段哲民, 龙英. 基于小波包的开关电流电路故障诊断. 工 程科学学报, 2017, 39(7):1101) [29] 李睿峰等: 基于空间近邻关系的非平衡数据重采样算法 · 869 ·
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