| Título | The metric-aware kernel-width choice for LIME |
|---|---|
| Autores | Barrera-Vicen A. , PALUZO HIDALGO, EDUARDO, Gutiérrez-Naranjo M.A. |
| Publicación externa | No |
| Medio | CEUR Workshop Proc. |
| Alcance | Conference Paper |
| Naturaleza | Científica |
| Impacto SJR | 0.191 |
| Web | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178587954&partnerID=40&md5=8f3f390d5ef84eb8f523b1325acdbd39 |
| Fecha de publicacion | 01/01/2023 |
| Scopus Id | 2-s2.0-85178587954 |
| Abstract | Local Interpretable Model-Agnostic Explanations (LIME) are a well-known approach to provide local interpretability to Machine Learning models. LIME uses an exponential smoothing kernel based on the kernel width value, which defines the width of the local neighbourhood. In this paper, we study the influence of the distances for these local explanations, and we explore the choice of kernel width to guarantee a fair performance comparison between the distances. © 2023 CEUR-WS. All rights reserved. |
| Palabras clave | Explainability; Exponential smoothing; Interpretability; Kernel width; Local interpretable model-agnostic explanation; Local neighborhoods; Machine learning models; Performance comparison; Smoothing kernels; XAI; Lime |
| Miembros de la Universidad Loyola |