Sullivan Hué
Biographic Data
| ID | 9595604 |
|---|---|
| NAME | Sullivan Hué |
| GIVEN NAMES | Sullivan |
| FAMILY NAME | Hué |
| SIGNATURE | HUE S |
| AFFILIATIONS | Aix‐Marseille University AMSE and CNRS Marseille France |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Interpretable Machine Learning Using Partial Linear Models
Despite their high predictive performance, random forest and gradient boosting are often considered as black boxes which has raised concerns from practitioners and regulators. As an alternative, we suggest using partial linear models that are inherently interpretable. Specifically, we propose to combine parametric and non‐parametric functions to accurately capture linearities and non‐linearities prevailing between dependent and explanatory variab…
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Interpretable Machine Learning Using Partial Linear Models
Despite their high predictive performance, random forest and gradient boosting are often considered as black boxes which has raised concerns from practitioners and regulators. As an alternative, we suggest using partial linear models that are inherently interpretable. Specifically, we propose to combine parametric and non‐parametric functions to accurately capture linearities and non‐linearities prevailing between dependent and explanatory variab…
Algorithm (1 work) · Artificial Intelligence (1 work) · Artificial neural network (1 work) · Computer Science (1 work) · Econometrics (1 work) · Ensemble learning (1 work) · Explainable Artificial Intelligence (XAI (1 work) · Feature selection (1 work) · Gradient boosting (1 work) · Interpretability (1 work)