Model parameterisation, testing and variations from Coupling machine learning and epidemiological modelling to characterize optimal fungicide doses when fungicide resistance is partial or quantitative
收藏DataCite Commons2023-04-11 更新2024-08-18 收录
下载链接:
https://rs.figshare.com/articles/dataset/Model_parameterisation_testing_and_variations_from_Coupling_machine_learning_and_epidemiological_modelling_to_characterize_optimal_fungicide_doses_when_fungicide_resistance_is_partial_or_quantitative/22586612
下载链接
链接失效反馈官方服务:
资源简介:
We present parameter values for the epidemiological model as well as the optimal hyperparameters for the gradient-boosted trees model. We evaluate the gradient-boosted trees model performance on both training and test data. We also present model variations which allow us to explore: the effect of model parameters within a single year only; the results in terms of cumulative yield over time; the effect of changing partial resistance parameterisation.
提供机构:
The Royal Society
创建时间:
2023-04-11



