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Several SVM Ensemble Methods Integrated with Under-Sampling for Imbalanced Data Learning
Advanced Data Mining and Applications - Lecture Notes in Computer Science
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10.1007/978-3-642-03348-3_54
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2009
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pp. 536-544
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Cited By ~ 10
Author(s):
ZhiYong Lin
◽
ZhiFeng Hao
◽
XiaoWei Yang
◽
XiaoLan Liu
Keyword(s):
Imbalanced Data
◽
Ensemble Methods
◽
Under Sampling
◽
Imbalanced Data Learning
Download Full-text
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Cited By
References
A Selective Under-Sampling based Bagging SVM for Imbalanced Data Learning in Biomedical Event Trigger Recognition
Proceedings of the 2nd International Conference on Biomedical Engineering and Bioinformatics - ICBEB 2018
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10.1145/3278198.3278221
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2018
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Author(s):
Yifei Chen
Keyword(s):
Imbalanced Data
◽
Event Trigger
◽
Under Sampling
◽
Imbalanced Data Learning
Download Full-text
An Under-Sampling Method with Support Vectors in Multi-class Imbalanced Data Classification
2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
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10.1109/skima47702.2019.8982391
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2019
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Cited By ~ 1
Author(s):
Md. Yasir Arafat
◽
Sabera Hoque
◽
Shuxiang Xu
◽
Dewan Md. Farid
Keyword(s):
Sampling Method
◽
Imbalanced Data
◽
Data Classification
◽
Support Vectors
◽
Imbalanced Data Classification
◽
Under Sampling
Download Full-text
An imbalanced data learning method for tool breakage detection based on generative adversarial networks
Journal of Intelligent Manufacturing
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10.1007/s10845-021-01806-y
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2021
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Author(s):
Shixu Sun
◽
Xiaofeng Hu
◽
Yingchao Liu
Keyword(s):
Imbalanced Data
◽
Generative Adversarial Networks
◽
Learning Method
◽
Tool Breakage
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Adversarial Networks
◽
Imbalanced Data Learning
Download Full-text
A Demand-Driven SAR Target Sample Generation Method for Imbalanced Data Learning
IEEE Transactions on Geoscience and Remote Sensing
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10.1109/tgrs.2021.3134674
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2021
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pp. 1-1
Author(s):
Changjie Cao
◽
Zongyong Cui
◽
Liying Wang
◽
Jielei Wang
◽
Zongjie Cao
◽
...
Keyword(s):
Imbalanced Data
◽
Target Sample
◽
Imbalanced Data Learning
Download Full-text
Data Mining Techniques in Direct Marketing on Imbalanced Data using Tomek Link Combined with Random Under-sampling
10.1145/3471287.3471299
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2021
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Author(s):
Ümit Yılmaz
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Cengiz Gezer
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Zafer Aydın
◽
V. Çağrı Güngör
Keyword(s):
Data Mining
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Direct Marketing
◽
Imbalanced Data
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Data Mining Techniques
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Under Sampling
Download Full-text
A Cluster-Based Under-Sampling Algorithm for Class-Imbalanced Data
Lecture Notes in Computer Science - Hybrid Artificial Intelligent Systems
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10.1007/978-3-030-61705-9_25
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2020
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pp. 299-311
Author(s):
A. Guzmán-Ponce
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R. M. Valdovinos
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J. S. Sánchez
Keyword(s):
Imbalanced Data
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Sampling Algorithm
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Under Sampling
Download Full-text
SBoost: A New Imbalanced Data Learning Algorithm
Journal of Convergence Information Technology
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10.4156/jcit.vol7.issue1.29
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2012
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Vol 7
(1)
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pp. 238-244
Author(s):
Yuanfang Dong
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Xiongfei Li
◽
Haiying Zhao
Keyword(s):
Learning Algorithm
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Imbalanced Data
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Imbalanced Data Learning
Download Full-text
Ensemble methods for strongly imbalanced data: bankruptcy prediction
2019 IEEE 17th International Symposium on Intelligent Systems and Informatics (SISY)
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10.1109/sisy47553.2019.9111557
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2019
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Author(s):
Peter Gnip
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Peter Drotar
Keyword(s):
Imbalanced Data
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Ensemble Methods
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Bankruptcy Prediction
Download Full-text
An under-sampling technique for imbalanced data classification based on DBSCAN algorithm
2020 8th Iranian Joint Congress on Fuzzy and intelligent Systems (CFIS)
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10.1109/cfis49607.2020.9238718
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2020
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Author(s):
Behzad Mirzaei
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Bahareh Nikpour
◽
Hossein Nezamabadi-Pour
Keyword(s):
Imbalanced Data
◽
Data Classification
◽
Sampling Technique
◽
Dbscan Algorithm
◽
Imbalanced Data Classification
◽
Under Sampling
Download Full-text
Ensemble based adaptive over-sampling method for imbalanced data learning in computer aided detection of microaneurysm
Computerized Medical Imaging and Graphics
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10.1016/j.compmedimag.2016.07.011
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2017
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Vol 55
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pp. 54-67
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Cited By ~ 29
Author(s):
Fulong Ren
◽
Peng Cao
◽
Wei Li
◽
Dazhe Zhao
◽
Osmar Zaiane
Keyword(s):
Sampling Method
◽
Imbalanced Data
◽
Computer Aided Detection
◽
Computer Aided
◽
Imbalanced Data Learning
Download Full-text
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