Sign inGet started
Paper · arXiv

IMEX Interaction-Based Model Explanation

In predictive modeling, the ability to explain why a model produces a given target prediction has become increasingly important [5, 10]. Black-box models do not provide a transparent description of the internal mechanisms that generate the prediction, making even accurate predictions difficult to interpret and validate. In critical contexts, predictive accuracy alone is not a sufficient validation metric if the reasons underlying model decisions remain unexplained. The IMEX (Interaction-Based Model Explanation) approach represents a methodological direction within explainable predictive modeling. IMEX is designed to identify which variables contribute most to the target prediction and whi...

AuthorsEmiliano Massi
Primary categorycs.AI
Published16 April 2026
Last updated at source16 April 2026
cs.AI
Embed this entry
<iframe src="https://silytics.si/embed/item/d8c2416a-d438-46fa-811c-ffab2d17e051" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.