Classification of Imbalanced Data by Oversampling in Kernel Space of Support Vector Machines

IEEE Transactions on Neural Networks and Learning Systems - Tập 29 Số 9 - Trang 4065-4076 - 2018
Josey Mathew1, Chee Khiang Pang1, Ming Luo2, Weng Hoe Leong3
1Department of Electrical and Computer Engineering, National University of Singapore, Singapore
2Singapore Institute of Manufacturing Technology, Singapore
3Hoestar Inspection International Pte Ltd., Singapore

Tóm tắt

Từ khóa


Tài liệu tham khảo

10.1109/ICPADM.2003.1218610

10.1109/TPWRD.2012.2200911

brown, 1996, Nonintrusive partial discharge measurements on high voltage switchgear, IEE Colloq Monitors Condition Assessment Equip, 10-1

alcalá-fdez, 2011, KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework, J Multiple-Valued Logic Soft Comput, 17, 255

demšar, 2006, Statistical comparisons of classifiers over multiple data sets, J Mach Learn Res, 7, 1

james, 2010, Latest Development in Partial Discharge Testing

10.1613/jair.953

he, 2008, ADASYN: Adaptive synthetic sampling approach for imbalanced learning, Proc Int Joint Conf Neural Netw, 1322

han, 2005, Borderline-SMOTE: A new over-sampling method in imbalanced data sets learning, Proc Int Conf Intell Comput, 878

10.1109/TCYB.2014.2344674

elkan, 2001, The foundations of cost-sensitive learning, Proc Int Joint Conf Artif Intell, 973

10.1016/j.neucom.2012.08.010

10.1109/TKDE.2006.17

10.1016/j.patcog.2007.04.009

veropoulos, 1999, Controlling the sensitivity of support vector machines, Proc Int Joint Conf Artif Intell, 55

akbani, 2004, Applying support vector machines to imbalanced datasets, Proc 15th Eur Conf Mach Learn, 39

10.1109/TASE.2006.888053

10.1007/978-3-642-40846-5_47

10.1109/TASE.2006.886833

zeng, 2009, Improving SVM classification with imbalance data set, Proc 16th Int Conf Neural Inf Process, 389

10.1109/72.991427

10.1023/A:1009715923555

10.1109/IECON.2015.7392251

10.1109/TKDE.2008.239

10.1109/TASE.2015.2470119

10.1109/TIE.2014.2327555

peng, 2010, Current status of machine prognostics in condition-based maintenance: A review, Int J Adv Manuf Technol, 50, 297, 10.1007/s00170-009-2482-0

10.1109/TPWRS.2006.888990

sun, 2006, Boosting for learning multiple classes with imbalanced class distribution, Proc Int Conf Data Mining, 592

10.1109/TNN.2006.882812

10.1109/TSMCB.2008.2002909

cristianini, 2001, On kernel target alignment, Proc Neural Inf Process Syst (NIPS), 367

imam, 2006, z-SVM: An SVM for Improved Classification of Imbalanced Data, Proc 19th Austral Joint Conf Artif Intell Adv, 264

10.18637/jss.v011.i09

rakotomamonjy, 2008, SimpleMKL, J Mach Learn Res, 9, 2491