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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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| Pubblicato in: | Bioinformatics |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Oxford University Press
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6041990/ https://ncbi.nlm.nih.gov/pubmed/29462247 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/bty087 |
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