1 code implementation • 3 Sep 2019 • Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Liyun He-Guelton, Olivier Caelen, Michael Granitzer, Sylvie Calabretto
Our multiple perspectives HMM-based approach offers automated feature engineering to model temporal correlations so as to improve the effectiveness of the classification task and allows for an increase in the detection of fraudulent transactions when combined with the state of the art expert based feature engineering strategy for credit card fraud detection.
no code implementations • 17 Jun 2019 • Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Liyun He-Guelton, Frederic Oblé, Michael Granitzer
This phenomenon is named dataset shift or concept drift in the domain of fraud detection.
1 code implementation • 15 May 2019 • Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Olivier Caelen, Liyun He-Guelton, Sylvie Calabretto, Michael Granitzer
In this article, we model a sequence of credit card transactions from three different perspectives, namely (i) does the sequence contain a Fraud?
no code implementations • 2 Jul 2015 • Léa Laporte, Rémi Flamary, Stephane Canu, Sébastien Déjean, Josiane Mothe
Feature selection in learning to rank has recently emerged as a crucial issue.