Comparative Analysis of Oversampling Techniques on Small and Imbalanced Datasets Using Deep Learning
Author:
Affiliation:
1. Islamic University of Science and Technology,Computer Science and Engineering,Kashmir,India
2. Islamic University of Science and Technology,Computer Science,Kashmir,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10134757/10134565/10134981.pdf?arnumber=10134981
Reference19 articles.
1. Distributional Random Oversampling for Imbalanced Text Classification
2. Data-efficient deep learning method for image classification using data augmentation, focal cosine loss, and ensemble;kim;arXiv preprint arXiv 2007 07047,2020
3. Borderline-smote: a new oversampling method in imbalanced data sets learning;han;Int Conf Intell Comput,2005
4. Smote: synthetic minority over-sampling technique;chawla;Journal of Artificial Intelligence Research,2002
5. Automatically countering imbalance and its empirical relationship to cost
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