When Two are Better Than One: Synthesizing Heavily Unbalanced Data

Nowadays, data is king and if treated and used properly it promises to give organizations a competitive edge over rivals by enabling them to develop and design Intelligent Systems to improve their services. However, they need to fully comply with not only ethical but also regulatory obligations, whe...

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Detalles Bibliográficos

Principais autores:	Francisco Ferreira, Nuno Lourenco, Bruno Cabral, Joao Paulo Fernandes
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2021-01-01
Series:	IEEE Access
Assuntos:	Fraud detection generative adversarial networks privacy machine learning synthetic data generation tabular data
Acceso en liña:	https://ieeexplore.ieee.org/document/9606863/
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