Annotation Sensitivity: Training Data Collection Methods Affect Model Performance

1 code implementation • 23 Nov 2023 • Christoph Kern, Stephanie Eckman, Jacob Beck, Rob Chew, Bolei Ma, Frauke Kreuter

We introduce the term annotation sensitivity to refer to the impact of annotation data collection methods on the annotations themselves and on downstream model performance and predictions.

SMART: An Open Source Data Labeling Platform for Supervised Learning

no code implementations • 11 Dec 2018 • Rob Chew, Michael Wenger, Caroline Kery, Jason Nance, Keith Richards, Emily Hadley, Peter Baumgartner

SMART is an open source web application designed to help data scientists and research teams efficiently build labeled training data sets for supervised machine learning tasks.

Active Learning BIG-bench Machine Learning