1 |
Chawla, N.V., Bowyer, K.W., Hall, L.O., and Kegelmeyer, W.P., SMOTE: Synthetic Minority Over-sampling Technique, Journal of Artificial Intelligence Research, 2002, Vol. 16, pp. 321-357.
DOI
|
2 |
Chen, Z., Yan, Q., Han, H., Wang, S., Peng, L., Wang, L., and Yang, B., Machine learning based mobile malware detection using highly imbalanced network traffic, Information Science, 2018, Vol. 433, pp. 346-364.
DOI
|
3 |
Cheong, Y.-G., Park, K., Kim, H., Kim, J., and Huun, S., Machine Learning Based Intrusion Detection Systems for Class Imbalanced Datasets, Journal of The Korea Institute of Information Security & Cryptology, 2017, Vol. 27, No. 6, pp. 1385-1395.
DOI
|
4 |
Han, H., Wang, W.-Y., and Mao B.-H., Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning, Proceedings of ICIC 2005: Advances in Intelligent Computing, 2005, pp. 878-887.
|
5 |
Jang, Y.S., Kim, J.W., and Hur, J., Combined Application of Data Imbalance Reduction Technique Using Genetic Algorithm, Journal of Intelligence and Information Systems, 2008, Vol. 14, No. 3, pp. 133-154.
|
6 |
Jung, H.N., Lee, J.-H., and Jun, C.-H., A Data Mining Procedure for Unbalanced Binary Classification, Journal of the Korean Institute of Industrial Engineers, 2010, Vol. 36, No. 1, pp. 13-21.
|
7 |
Kim, H.S. and Lee, H.S., Generative Adversarial Networks based Data Generation Framework for Overcoming Imbalanced Manufacturing Process Data, J. of Korean Ins. of Intell. Syst., 2019, Vol. 29, No. 1, pp. 1-8.
DOI
|
8 |
Kirkpatrick, S., Gelatt, C.D., and Vecchi, M.P., Optimization by Simulated Annealing, Science, 1983, Vol. 220, No. 4598, pp. 671-680.
DOI
|
9 |
Lee, J.S. and Kwon, J.G., A Hybrid SVM Classifier for Imbalanced Data Sets, J. Intell. Inform. Syst., 2013, Vol. 19, No. 2, pp. 125-140.
DOI
|
10 |
Lee, K.N., Lim, J., Bok, K., and Yoo, J., Handling Method of Imbalance Data for Machine Learning : Focused on Sampling, The Journal of the Korea Contents Association, 2019, Vol. 19, No. 11, pp. 567-577.
DOI
|
11 |
Ministry of SMEs and Startups, Korea AI Manufacturing Platform(KAMP), CNC Machine AI Dataset, KAIST(UNIST, EPM Solutions), 2020.12.14., https://kamp-ai.kr.
|
12 |
Shin, S.S., Cho, H.Y., and Kim, Y.H., Optimal Ratio of Data Oversampling Based on a Genetic Algorithm for Overcoming Data Imbalance, J. of the Korea Convergence Society, 2021, Vol. 12, No. 1, pp. 49-55.
DOI
|
13 |
Son, M.J., Jung, S.W., and Hwang, E.J., A Deep Learning Based Over-Sampling Scheme for Imbalanced Data Classification, KIPS Trans. Softw. And Data Eng., 2019, Vol. 8, No. 7, pp. 311-316.
DOI
|