A Hybrid SMOTE–GAN Approach for Optimizing Fraud Detection Model Performance
- 2 July 2026
- book chapter
- Published by Springer Nature
- p. 13-22
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- Creating synthetic datasets for collaborative filtering recommender systems using generative adversarial networksKnowledge-Based Systems, 2023
- Data Preparation: A Technological Perspective and ReviewSN Computer Science, 2023
- An easy numeric data augmentation method for early-stage COVID-19 tweets exploration of participatory dynamics of public attention and news coverageInformation Processing & Management, 2022
- A Comparative Performance Analysis of Data Resampling Methods on Imbalance Medical DataIEEE Access, 2021
- Relevant information undersampling to support imbalanced data classificationNeurocomputing, 2021
- Understanding the apparent superiority of over-sampling through an analysis of local information for class-imbalanced dataExpert Systems with Applications, 2020
- Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparitiesnpj Digital Medicine, 2020
- Systematic literature review of preprocessing techniques for imbalanced dataIET Software, 2019
- An Experimental Study With Imbalanced Classification Approaches for Credit Card Fraud DetectionIEEE Access, 2019
- Learning from class-imbalanced data: Review of methods and applicationsExpert Systems with Applications, 2017