3 papers
stat.ML2026
How important are the genes to explain the outcome - the asymmetric Shapley value as an honest importance metric for high-dimensional features
Mark A. van de Wiel, Jeroen Goedhart, Martin Jullum +1
In clinical prediction settings the importance of a high-dimensional feature like genomics is often assessed by evaluating the change in predictive performance when adding it to a…
q-fin.RM2024
Multimodal Generative Models for Bankruptcy Prediction Using Textual Data
Rogelio A. Mancisidor, Kjersti Aas
Textual data from financial filings, e.g., the Management's Discussion & Analysis (MDA) section in Form 10-K, has been used to improve the prediction accuracy of bankruptcy models.…
stat.ML2024
MCCE: Monte Carlo sampling of realistic counterfactual explanations
Annabelle Redelmeier, Martin Jullum, Kjersti Aas +1
We introduce MCCE: Monte Carlo sampling of valid and realistic Counterfactual Explanations for tabular data, a novel counterfactual explanation method that generates on-manifold, a…