Cargando…
Explainable Model Fusion for Customer Journey Mapping
Due to advances in computing power and internet technology, various industrial sectors are adopting IT infrastructure and artificial intelligence (AI) technologies. Recently, data-driven predictions have attracted interest in high-stakes decision-making. Despite this, advanced AI methods are less of...
Autores principales: | Okazaki, Kotaro, Inoue, Katsumi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131849/ https://www.ncbi.nlm.nih.gov/pubmed/35647530 http://dx.doi.org/10.3389/frai.2022.824197 |
Ejemplares similares
-
Benchmarking Perturbation-Based Saliency Maps for Explaining Atari Agents
por: Huber, Tobias, et al.
Publicado: (2022) -
Artificial intelligence assisted acute patient journey
por: Nazir, Talha, et al.
Publicado: (2022) -
No silver bullet: interpretable ML models must be explained
por: Marques-Silva, Joao, et al.
Publicado: (2023) -
Editorial: Explainable artificial intelligence models and methods in finance and healthcare
por: Caffo, Brian S., et al.
Publicado: (2022) -
Corrigendum: Editorial: Explainable artificial intelligence models and methods in finance and healthcare
por: Caffo, Brian S., et al.
Publicado: (2023)