This project list resources on the topic of Machine Learning for Credit Card Fraud Detection.
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Credit Card Fraud Detection: a Realistic Modeling and a Novel Learning Strategy A. Dal Pozzolo, G. Boracchi, O. Caelen, C. Alippi and G. Bontempi, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2017. pdf
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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.
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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
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Feature engineering strategies for credit card fraud detection AC Bahnsen, D Aouada, A Stojanovic, B Ottersten, Expert Systems with Applications 51, 134-142, 2016
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Ensemble of Example-Dependent Cost-Sensitive Decision Trees AC Bahnsen, D Aouada, B Ottersten, arXiv preprint arXiv:1505.04637, 2015
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Example-dependent cost-sensitive decision trees AC Bahnsen, D Aouada, B Ottersten, Expert Systems with Applications 42 (19), 6609-6619, 2015
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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
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Detecting Credit Card Fraud using Periodic Features AC Bahnsen, D Aouada, A Stojanovic, 2015 IEEE 14th International Conference on Machine Learning and Applications.
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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. pdf
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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
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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
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Cost sensitive credit card fraud detection using Bayes minimum risk AC Bahnsen, A Stojanovic, D Aouada, B Ottersten, Machine Learning and Applications (ICMLA), 2013
- Fraud Analytics: Using Supervised, Unsupervised and Social Network Learning Techniques Bart Baesens, Véronique Van Vlasselaer, Wouter Verbeke, Amazon
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Adaptive Machine Learning for Credit Card Fraud Detection A. Dal Pozzolo, Universite Libre de Bruxelles, 2015. pdf
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Example-Dependent Cost-Sensitive Classification AC Bahnsen, University of Luxembourg, 2015.
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FAIR: Forecasting and network analytics for collection risk management V. Van Vlasselaer, Katholieke Universiteit Leuven, 2015.