Enhancing Financial Fraud Detection through Addressing Class Imbalance Using Hybrid SMOTE-GAN Techniques

Keyphrases

• Affective Classification 14%
• Class Imbalance 100%
• Class Imbalance Issue 14%
• Class Imbalance Problem 14%
• Classification Performance 14%
• Convolutional Neural Network 28%
• Credit Card Fraud Detection 100%
• Feedforward Neural Network 14%
• Forward Neural Network 14%
• Fraud 42%
• Generation Method 28%
• Generative Adversarial Networks 100%
• Hyperparameters 14%
• Network Technique 100%
• Poor Performance 14%
• Synthetic Minority Oversampling Technique (SMOTE) 100%

Computer Science

• Applied Technique 14%
• Class Imbalance 100%
• Class Imbalance Problem 14%
• Classification Performance 14%
• Convolutional Neural Network 28%
• Data Generation 28%
• Feed Forward Neural Networks 14%
• Feedforward Neural Network 14%
• Forward Neural Network 14%
• Fraud Detection 100%
• Generative Adversarial Networks 100%