I am trying to increase size a numeric dataset that I have been working with. The dataset comprises the columns: [‘Name’, ‘O3_1hr’, ‘O3_4hr’, ‘O3_8hr’, ‘PM10 1 hr’, ‘PM10’, ‘AQI_O3_1hr’, ‘AQI_O3_4hr’, ‘AQI_PM10’, ‘AQI_Site’, ‘Date’, ‘Time’, ‘Latitude’, ‘Longitude’].
Previously, I attempted to use a GAN (Generative Adversarial Network) for data augmentation, which yielded an accuracy of 87%. This accuracy is not acceptable.
I would greatly appreciate any guidance or recommendations in this regard. Specifically, I am interested in alternative methods of data augmentation or any other techniques that can effectively expand a numeric dataset while preserving the integrity and patterns that already exist in the data.