A machine learning based credit card fraud detection using the GA algorithm for feature selection
University of Johannesburg · University of South Africa
Abstract
Abstract The recent advances of e-commerce and e-payment systems have sparked an increase in financial fraud cases such as credit card fraud. It is therefore crucial to implement mechanisms that can detect the credit card fraud. Features of credit card frauds play important role when machine learning is used for credit card fraud detection, and they must be chosen properly. This paper proposes a machine learning (ML) based credit card fraud detection engine using the genetic algorithm (GA) for feature selection. After the optimized features are chosen, the proposed detection engine uses the following ML classifiers: Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Artificial Neural Network…
Citation impact
- FWCI
- 44.39
- Percentile
- 100%
- References
- 25
Authors
3Topics & keywords
- Credit card fraud
- Credit card
- Computer science
- Feature selection
- Random forest
- Machine learning
- Naive Bayes classifier
- Artificial intelligence
- Peace, Justice and strong institutions