Prediction of radionuclide diffusion enabled by missing data imputation and ensemble machine learning
收藏DataCite Commons2025-05-06 更新2025-05-18 收录
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资源简介：
Missing values in radionuclide diffusion datasets can undermine the predictive accuracy and robustness of machine learning models. A regression-based missing data imputation method using light gradient boosting machine algorithm was employed to impute over 60% of the missing data.
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Science Data Bank
创建时间：
2025-05-06
