Developing interpretable machine learning-Shapley additive explanations model for unconfined compressive strength of cohesive soils stabilized with geopolymer

This paper seeks to develop an interpretable Machine Learning (ML) model for predicting the unconfined compressive strength (UCS) of cohesive soils stabilized with geopolymer at 28 days. Four models including Random Forest (RF), Artificial Neuron Network (ANN), Extreme Gradient Boosting (XGB), and G...

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Detalles Bibliográficos
Autores principales: Ngo, Anh Quan, Nguyen, Linh Quy, Tran, Van Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249854/
https://www.ncbi.nlm.nih.gov/pubmed/37289821
http://dx.doi.org/10.1371/journal.pone.0286950

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249854/
https://www.ncbi.nlm.nih.gov/pubmed/37289821
http://dx.doi.org/10.1371/journal.pone.0286950

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