Zhenhua He, Lifeng Chen, Lianqin Zhu
A study of Inter-Technology Information Management (ITIM) system for industry-education integration
Heliyon
rapid advances machine learning ml provide fast accurate widely applicable methods predicting free radicalmediated organic pollutant reactivity study rate constants logk four halogen radicals predicted using morgan fingerprint mf mordred descriptor md combination series ml models findings highlighted making accurate predictions various datasets depended effective combination descriptors algorithms alleviate challenge limited sample size introduced data combination strategy improved prediction accuracy mitigated overfitting combining different datasets light gradient boosting machine lightgbm mf random forest rf md models based unified dataset finally selected optimal models shapley additive explanations revealed insights mflightgbm model successfully captured influence electronwithdrawingdonating groups autocorrelation walk count information content descriptors mdrf model identified key features furthermore important contribution ph emphasized results applicability domain analysis supported developed model make reliable predictions query compounds across broader range finally practical web application logk calculations built