Cargando…
Hierarchical confounder discovery in the experiment-machine learning cycle
The promise of machine learning (ML) to extract insights from high-dimensional datasets is tempered by confounding variables. It behooves scientists to determine if a model has extracted the desired information or instead fallen prey to bias. Due to features of natural phenomena and experimental des...
| Autores principales: | , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024009/ https://www.ncbi.nlm.nih.gov/pubmed/35465234 http://dx.doi.org/10.1016/j.patter.2022.100451 |