Search Results for author:
Found 1 papers, 0 papers with code
Inter-annotator agreement is not the ceiling of machine learning performance: Evidence from a comprehensive set of simulations
It is commonly claimed that inter-annotator agreement (IAA) is the ceiling of machine learning (ML) performance, i. e., that the agreement between an ML system’s predictions and an annotator can not be higher than the agreement between two annotators.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
