no code implementations • 30 Mar 2022 • Rafael Poyiadzi, Daniel Bacaicoa-Barber, Jesus Cid-Sueiro, Miquel Perello-Nieto, Peter Flach, Raul Santos-Rodriguez
In this paper we propose a framework for categorising weak supervision settings with the aim of: (1) helping the dataset owner or annotator navigate through the available options within weak supervision when prescribing an annotation process, and (2) describing existing annotations for a dataset to machine learning practitioners so that we allow them to understand the implications for the learning process.