Synthetic fraud data

This repository contains a preprocessed version of the synthetic fraud dataset published in: 

Padhi, I., Schiff, Y., Melnyk, I., Rigotti, M., Mroueh, Y., Dognin, P., ... & Altman, E. (2021, June). Tabular transformers for modeling multivariate time series. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3565-3569). IEEE.

The original dataset can be accessed here

The subsets are arranged in a rolling window. Each training subset contains 300 days of transaction data. The test sets contain 60 days of data. These subsets are intended for use with SHINE (https://github.com/rafaelvanbelle/SHINE/)