On Efficient and Statistical Quality Estimation for Data Annotation

Annotated data is an essential ingredient to train, evaluate, compare and productionalize machine learning models. It is therefore imperative that annotations are of high quality. For their creation, good quality management and thereby reliable quality estimates are needed. Then, if quality is insufficient during the annotation process, rectifying measures can be taken to improve it. For instance, project managers can use quality estimates to improve annotation guidelines, retrain annotators or catch as many errors as possible before release.
Quality estimation is often performed by having…Apple Machine Learning Research