Searching for Anomalous Subsets? All You Need is Scanning- Tanya Akumu | SciPy 2022
Analysts and decision makers seek to understand their data at a subset level as this can reveal insights that are not apparent at global (all records) or local (single record) levels. Unfortunately, there are exponentially-many subsets to consider, and undisciplined, manual inspection covers a tiny fraction of the possibilities. This talk will step through multiple use cases of Subset Scanning and use it to efficiently detect vulnerable/privileged subgroups and detect bias in predictive classification models at the subset level. The code is part of the Linux Foundation’s AI Fairness 360 Toolkit https://ai-fairness-360.org/.
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