Prediction of radionuclide diffusion enabled by missing data imputation and ensemble machine learning
收藏科学数据银行2025-05-06 更新2026-04-23 收录
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https://www.scidb.cn/detail?dataSetId=375765a4001d43e5b41efa373c69954f
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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.
提供机构：
Jun-Lei Tian; Huzhou University; Jia-Cong Shen; Xi'an Jiaotong University
创建时间：
2025-05-06
