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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...
Autores principales: | Wenck, Soeren, Creydt, Marina, Hansen, Jule, Gärber, Florian, Fischer, Markus, Seifert, Stephan |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
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 |
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