Synthetic Outliers Evaluation

The Synthetic Outliers Evaluation task aims to assess the quality and utility of synthetic data containing outliers in machine learning. Outliers generated through Extreme Value Theory (EVT) can simulate rare events, enhancing the realism and predictive performance of the data, while also aiding in the detection, handling, and removal of outliers in real datasets. This task falls under the Miscellaneous category and holds significant research and application value.