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A Novel Boundary Oversampling Algorithm Based on Neighborhood Rough Set Model: NRSBoundary-SMOTE
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-11
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Rough set theory is a powerful mathematical tool introduced by Pawlak to deal with imprecise, uncertain, and vague information.
The Neighborhood-Based Rough Set Model expands the rough set theory; it could divide the dataset into three parts.
And the boundary region indicates that the majority class samples and the minority class samples are overlapped.
On the basis of what we know about the distribution of original dataset, we only oversample the minority class samples, which are overlapped with the majority class samples, in the boundary region.
So, the NRSBoundary-SMOTE can expand the decision space for the minority class; meanwhile, it will shrink the decision space for the majority class.
After conducting an experiment on four kinds of classifiers, NRSBoundary-SMOTE has higher accuracy than other methods when C4.5, CART, and KNN are used but it is worse than SMOTE on classifier SVM.
American Psychological Association (APA)
Hu, Feng& Li, Hang. 2013. A Novel Boundary Oversampling Algorithm Based on Neighborhood Rough Set Model: NRSBoundary-SMOTE. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1032086
Modern Language Association (MLA)
Hu, Feng& Li, Hang. A Novel Boundary Oversampling Algorithm Based on Neighborhood Rough Set Model: NRSBoundary-SMOTE. Mathematical Problems in Engineering No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-1032086
American Medical Association (AMA)
Hu, Feng& Li, Hang. A Novel Boundary Oversampling Algorithm Based on Neighborhood Rough Set Model: NRSBoundary-SMOTE. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1032086
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032086