Hybrid Undersampling and Oversampling for Handling Imbalanced Credit Card Data
Author:
Affiliation:
1. Information System Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia
Funder
“Research Center of the Female Scientific and Medical Colleges,” Deanship of Scientific Research, King Saud University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10411884.pdf?arnumber=10411884
Reference31 articles.
1. Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset
2. Predicting credit card fraud on a imbalanced data;Soh;Int. J. Data Sci. Adv. Anal.,2019
3. Comparing the Behavior of Oversampling and Undersampling Approach of Class Imbalance Learning by Combining Class Imbalance Problem with Noise
4. Improving Fraud Detection in An Imbalanced Class Distribution Using Different Oversampling Techniques
5. Detection of fraudulent credit card transactions: A comparative analysis of data sampling and classification techniques
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