Amit Somech

Extracting Explainable Temporal Features in Multivariate Time Series Classification Pipelines

EFFECTS is introduced, a scalable framework for extracting interpretable temporal features that enable model-agnostic explanations of black-box classifiers and also support the construction of inherently interpretable models.