Label Error Detection

Label Error Detection is an important subtask within the Miscellaneous tasks, aiming to identify label errors present in datasets. This task involves analyzing the inconsistencies between the features and labels of the data, enhancing data quality, and ensuring the training effectiveness and generalization ability of machine learning models. Accurately detecting and correcting label errors during the data preprocessing stage is crucial for improving model performance.