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Random generalized linear model: a highly accurate and interpretable ensemble predictor
BACKGROUND: Ensemble predictors such as the random forest are known to have superior accuracy but their black-box predictions are difficult to interpret. In contrast, a generalized linear model (GLM) is very interpretable especially when forward feature selection is used to construct the model. Howe...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2013
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3645958/ https://ncbi.nlm.nih.gov/pubmed/23323760 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-14-5 |
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