tehreemansari / machine-learning-for-credit-card-fraud-detection

Adaptive Machine Learning for Credit Card Fraud Detection

Adaptive Machine Learning for Credit Card Fraud Detection

This project list resources on the topic of Machine Learning for Credit Card Fraud Detection.

Publications

• GOTCHA! Network-based fraud detection for social security fraud Van Vlasselaer, V., Eliassi-Rad, T., Akoglu, L., Snoeck, M., Baesens, B., Management Science, accepted 2017.

• A graph-based, semi-supervised, credit card fraud detection system B. Lebichot, F. Braun, and O. Caelen and M. Saerens, International Workshop on Complex Networks and their Applications, 721--733, 2016. Springer

• Feature engineering strategies for credit card fraud detection AC Bahnsen, D Aouada, A Stojanovic, B Ottersten, Expert Systems with Applications 51, 134-142, 2016

• Ensemble of Example-Dependent Cost-Sensitive Decision Trees AC Bahnsen, D Aouada, B Ottersten, arXiv preprint arXiv:1505.04637, 2015

• Example-dependent cost-sensitive decision trees AC Bahnsen, D Aouada, B Ottersten, Expert Systems with Applications 42 (19), 6609-6619, 2015

• APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions. Van Vlasselaer V., Bravo C., Caelen O., Eliassi-Rad T., Akoglu L., Snoeck M., Baesens B., Decision Support Systems. 2015. Elsevier

• Detecting Credit Card Fraud using Periodic Features AC Bahnsen, D Aouada, A Stojanovic, 2015 IEEE 14th International Conference on Machine Learning and Applications.

• Credit Card Fraud Detection and Concept-Drift Adaptation with Delayed Supervised Information A. Dal Pozzolo, G. Boracchi, O. Caelen, C. Alippi and G. Bontempi, International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, 2015. 2014. pdf

• Learned lessons in credit card fraud detection from a practitioner perspective A. Dal Pozzolo, O. Caelen, Y. Le Borgne, S. Waterschoot, and G. Bontempi, Expert Systems with Applications, vol. 41, no. 10, pp. 4915–4928, 2014. pdf

• Using HDDT to avoid instances propagation in unbalanced and evolving data streams A. Dal Pozzolo, R. A Johnson, O. Caelen, S. Waterschoot, N. V Chawla, and G. Bontempi, International Joint Conference on Neural Networks (IJCNN), Beijing, China, 2014. pdf

• Cost sensitive credit card fraud detection using Bayes minimum risk AC Bahnsen, A Stojanovic, D Aouada, B Ottersten, Machine Learning and Applications (ICMLA), 2013

Books

• Fraud Analytics: Using Supervised, Unsupervised and Social Network Learning Techniques Bart Baesens, Véronique Van Vlasselaer, Wouter Verbeke, Amazon

Thesis

• Adaptive Machine Learning for Credit Card Fraud Detection A. Dal Pozzolo, Universite Libre de Bruxelles, 2015. pdf

• Example-Dependent Cost-Sensitive Classification AC Bahnsen, University of Luxembourg, 2015.

• FAIR: Forecasting and network analytics for collection risk management V. Van Vlasselaer, Katholieke Universiteit Leuven, 2015.

Dataset

• https://www.kaggle.com/dalpozz/creditcardfraud