Cargando…
A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys
We demonstrate the capabilities of two model-agnostic local post-hoc model interpretability methods, namely breakDown (BD) and shapley (SHAP), to explain the predictions of a black-box classification learning model that establishes a quantitative relationship between chemical composition and multi-p...
| Autores principales: | , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270422/ https://www.ncbi.nlm.nih.gov/pubmed/35804179 http://dx.doi.org/10.1038/s41598-022-15618-4 |