What is label flagging?

Label flagging is a process used in data annotation and machine learning where specific labels or tags assigned to data points are identified as potentially incorrect or problematic. This is often done to ensure data quality and improve the accuracy of machine learning models. Flagging allows for the review and correction of labels, helping to refine the dataset and enhance model performance. It is particularly important in tasks involving sensitive or nuanced data, such as image or text classification.