GAMC: An Oversampling Method Based on Genetic Algorithm and Monte Carlo Method to Solve the Class Imbalance Issue in Industry
Author:
Affiliation:
1. Chongqing University of Posts and Telecommunications,Chongqing Key Laboratory of Computational Intelligence,Chongqing,China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Chongqing
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10077107/10077082/10077154.pdf?arnumber=10077154
Reference21 articles.
1. Downsampling for Binary Classification with a Highly Imbalanced Dataset Using Active Learning
2. MMD-encouraging convolutional autoencoder: a novel classification algorithm for imbalanced data
3. Binary imbalanced data classification based on diversity oversampling by generative models
4. SMOTE: Synthetic Minority Over-sampling Technique
5. ADASYN: Adaptive synthetic sampling approach for imbalanced learning.;he;IEEE Int Conf Neural Netw,2008
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