"Probabilistic Random Forest improves bioactivity predictions close to the ..."

Lewis H. Mervin et al. (2021)

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DOI: 10.1186/S13321-021-00539-7

access: open

type: Journal Article

metadata version: 2022-10-02

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Lewis H. Mervin, Maria-Anna Trapotsi, Avid M. Afzal, Ian P. Barrett, Andreas Bender, Ola Engkvist:
Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty. J. Cheminformatics 13(1): 62 (2021)

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