DivExplorer is a tool for analyzing datasets and finding subgroups of data where a classifier behaves differently than on the overall data.
Useful links:
Publications
- Looking for Trouble: Analyzing Classifier Behavior via Pattern Divergence. Eliana Pastor, Luca de Alfaro, Elena Baralis. In Proceedings of the 2021 International Conference on Management of Data (SIGMOD ’21), 1400–1412. June 20–25, 2021, Virtual Event, China.
- How Divergent Is Your Data?. Eliana Pastor, Andrew Gavgavian, Elena Baralis, and Luca de Alfaro. In Proceedings of the 47th International Conference on Very Large Data Bases (VLDB), Demo Track, 2021. PVLDB, 14(12).