69 citations · 69 across the 2 of their papers we have counts for
2 papers
cs.LG2024
On Efficient and Statistical Quality Estimation for Data Annotation
Jan-Christoph Klie, Juan Haladjian, Marc Kirchner +1
Annotated datasets are an essential ingredient to train, evaluate, compare and productionalize supervised machine learning models. It is therefore imperative that annotations are o…
cs.HC2021★ 69 cited
Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels
Jochen Görtler, Fred Hohman, Dominik Moritz +5
The confusion matrix, a ubiquitous visualization for helping people evaluate machine learning models, is a tabular layout that compares predicted class labels against actual class…