Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AI

Understand

Machine learning (ML) on tabular data is ubiquitous, yet obtaining abundant high-quality tabular data for model training remains a significant obstacle.

• Numerous works have focused on tabular data augmentation (TDA) to enhance the original table with additional data, thereby improving downstream ML tasks.
• Recently, there has been a growing interest in leveraging the capabilities of generative AI for TDA.
• Therefore, we believe it is time to provide a comprehensive review of the progress and future prospects of TDA, with a particular emphasis on the trending generative AI.