Graph-Powered Interpretable Machine Learning Models for Abnormality Detection in Ego-Things Network

In recent days, it is becoming essential to ensure that the outcomes of signal processing methods based on machine learning (ML) data-driven models can provide interpretable predictions. The interpretability of ML models can be defined as the capability to understand the reasons that contributed to...

Descripción completa

Detalles Bibliográficos
Autores principales: Thekke Kanapram, Divya, Marcenaro, Lucio, Martin Gomez, David, Regazzoni, Carlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8953755/
https://www.ncbi.nlm.nih.gov/pubmed/35336431
http://dx.doi.org/10.3390/s22062260

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8953755/
https://www.ncbi.nlm.nih.gov/pubmed/35336431
http://dx.doi.org/10.3390/s22062260

Ejemplares similares