Synthetic Outliers Evaluation

The Synthetic Outliers Evaluation task aims to assess the quality and utility of synthetic tabular data containing outliers. This task enhances the realism of the data by generating outliers based on Extreme Value Theory (EVT), improves the predictive performance of machine learning models, and facilitates the detection, handling, and removal of outliers in real-world data. Such evaluation is crucial for enhancing the reliability of data-driven decision-making.