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Publication Materials for "Extending Approximate Bayesian Computation with Supervised Machine Learning to Infer Demographic History from Genetic Polymorphisms Using DIYABC Random Forest" in *Molecular Ecology Resources* special issue

Home Page: https://diyabc.github.io

License: MIT License

machine-learning population-genetics approximate-bayesian-computation random-forest model-choice parameter-estimation shiny-apps

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Publication materials for

Collin F-D, Durif G, Raynal L, Gautier M, Vitalis R, Lombaert E., Marin J-M, Estoup A., 2021, Extending Approximate Bayesian Computation with Supervised Machine Learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest. Molecular Ecology Resources, Wiley/Blackwell, 21(8), pp. 2598โ€“2613. <doi/10.1111/1755-0998.13413> <hal-03229207>

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