Exploring Innovative Approaches to Synthetic Tabular Data Generation
Eugenia Papadaki,
Aristidis G. Vrahatis,
Sotiris Kotsiantis
Abstract:The rapid advancement of data generation techniques has spurred innovation across multiple domains. This comprehensive review delves into the realm of data generation methodologies, with a keen focus on statistical and machine learning-based approaches. Notably, novel strategies like the divide-and-conquer (DC) approach and cutting-edge models such as GANBLR have emerged to tackle a spectrum of challenges, spanning from preserving intricate data relationships to enhancing interpretability. Furthermore, the int… Show more
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