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Welcome to ADVO
===============

This library contains the code for the research paper "An adversary model of fraudsters' behaviour to improve oversampling in credit card fraud detection." The paper presents a new approach to detecting credit card fraud by using an adversary model to simulate the behavior of fraudsters. This approach is designed to improve the effectiveness of oversampling techniques, which are commonly used in credit card fraud detection to balance the imbalanced dataset of fraudulent and non-fraudulent transactions.

The main contribution of the paper is the development of a novel adversary model that is able to learn the behavior of fraudsters and generate synthetic fraudulent transactions that are representative of the true distribution of fraudulent transactions in the dataset. By using this model, it is possible to generate a more balanced dataset that is better suited for training fraud detection models. The paper also presents experimental results showing the effectiveness of this approach on several real-world datasets.

Overall, this library provides a useful resource for researchers and practitioners interested in improving the effectiveness of credit card fraud detection through the use of adversary models and oversampling techniques.

Contents
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.. toctree::
   :maxdepth: 1

   genindex
   usage
   modules
   about