A new approach for interpreting Random Forest models and its application to the biology of ageing

MOTIVATION: This work uses the Random Forest (RF) classification algorithm to predict if a gene is over-expressed, under-expressed or has no change in expression with age in the brain. RFs have high predictive power, and RF models can be interpreted using a feature (variable) importance measure. How...

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Detalles Bibliográficos
Autores principales: Fabris, Fabio, Doherty, Aoife, Palmer, Daniel, de Magalhães, João Pedro, Freitas, Alex A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6041990/
https://www.ncbi.nlm.nih.gov/pubmed/29462247
http://dx.doi.org/10.1093/bioinformatics/bty087

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6041990/
https://www.ncbi.nlm.nih.gov/pubmed/29462247
http://dx.doi.org/10.1093/bioinformatics/bty087

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