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Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset
Research article (2020 IEEE 16th International Conference on Control & Automation (ICCA), 2020) · cited 71× · AI/ML
Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset
Summary
Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset is a scholarly article[1].
Key Facts
Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset. Retrieved May 24, 2026, from https://4ort.xyz/entity/combining-oversampling-and-undersampling-techniques-for-imbalanced-classification-a-comparative-study-using-credit-card-
MLA“Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/combining-oversampling-and-undersampling-techniques-for-imbalanced-classification-a-comparative-study-using-credit-card-.
BibTeX@misc{4ortxyz_combining-oversampling-and-undersampling-techniques-for-imbalanced-classification-a-comparative-study-using-credit-card-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset}}, year = {2026}, url = {https://4ort.xyz/entity/combining-oversampling-and-undersampling-techniques-for-imbalanced-classification-a-comparative-study-using-credit-card-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset — https://4ort.xyz/entity/combining-oversampling-and-undersampling-techniques-for-imbalanced-classification-a-comparative-study-using-credit-card- (retrieved 2026-05-24)
