LR-SMOTE — An improved unbalanced data set oversampling based on K-means and SVM-Reference-Cited by-同舟云学术

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LR-SMOTE — An improved unbalanced data set oversampling based on K-means and SVM

Published:2020-05 Issue: Volume:196 Page:105845
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Liang X.W.,Jiang A.P.,Li T.,Xue Y.Y.,Wang G.T.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Heilongjiang Province

Postdoctoral Fund in Heilongjiang Province

Talent Innovation Special Project of Heilongjiang Province

Science and Technology Innovative Research Team in Higher Educational Institutions of Heilongjiang Province

Heilongjiang University Youth Science Fund

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference42 articles.

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2. Association rule mining-based dissolved gas analysis for fault diagnosis of power transformers;Yang;IEEE Trans. Syst. Man Cybern. C,2009

3. Face recognition using total margin-based adaptive fuzzy support vector machines;Liu;IEEE Trans. Neural Netw.,2007

4. An overview of classification algorithms for imbalanced datasets;Ganganwar;Int. J. Emerg. Technol. Adv. Eng.,2012

5. Cluster-based weighted oversampling for ordinal regression (cwos-ord);Nekooeimehr;Neurocomputing,2016

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