Opening the Random Forest Black Box of the Metabolome by the Application of Surrogate Minimal Depth

For the untargeted analysis of the metabolome of biological samples with liquid chromatography–mass spectrometry (LC-MS), high-dimensional data sets containing many different metabolites are obtained. Since the utilization of these complex data is challenging, different machine learning approaches h...

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Detalles Bibliográficos
Autores principales: Wenck, Soeren, Creydt, Marina, Hansen, Jule, Gärber, Florian, Fischer, Markus, Seifert, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8781913/
https://www.ncbi.nlm.nih.gov/pubmed/35050127
http://dx.doi.org/10.3390/metabo12010005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8781913/
https://www.ncbi.nlm.nih.gov/pubmed/35050127
http://dx.doi.org/10.3390/metabo12010005

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