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cs.LG2024
Case-based Explainability for Random Forest: Prototypes, Critics, Counter-factuals and Semi-factuals
Gregory Yampolsky, Dhruv Desai, Mingshu Li +2
The explainability of black-box machine learning algorithms, commonly known as Explainable Artificial Intelligence (XAI), has become crucial for financial and other regulated indus…
cs.LG2024
Open Set Recognition for Random Forest
Guanchao Feng, Dhruv Desai, Stefano Pasquali +1
In many real-world classification or recognition tasks, it is often difficult to collect training examples that exhaust all possible classes due to, for example, incomplete knowled…