HIEF: An Interpretable Evidence-Fusion Framework for Phishing Email Detection with Decomposable Decision Uncertainty and a Preliminary English–Spanish Evaluation
This work asks how far a fully interpretable detector can close the accuracy gap to an opaque text classifier while preserving per-decision explanations, and what such a detector returns that accuracy alone does not measure.
Carolina Del-Valle-Soto, Carlos-Santiago Cruz-Diaz, Manuel Cardona et al.
· Algorithms · 0 citations