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Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection
Among these methods, Kernel SHAP is widely used due to its model-agnostic nature and its well-founded theoretical framework.
Persistence-Based Discretization for Learning Discrete Event Systems from Time Series
After the study of the persistence score, we point out that it tends to favor excessive cases making it miss interesting persisting symbols.
s-LIME: Reconciling Locality and Fidelity in Linear Explanations
The benefit of locality is one of the major premises of LIME, one of the most prominent methods to explain black-box machine learning models.
Day-ahead time series forecasting: application to capacity planning
In the context of capacity planning, forecasting the evolution of informatics servers usage enables companies to better manage their computational resources.
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