Optimal selection of learning data for highly accurate QSAR prediction of chemical biodegradability: a machine learning-based approach

In this study, we propose a novel approach for the optimal selection of training set that enables a highly accurate prediction of the biodegradability of chemicals by QSAR. Our findings indicate that the proposed method effectively reduces the root mean squared error and improves the prediction accuracy.PMID:37674414 | DOI:10.1080/1062936X.2023.2251889

Source: SAR and QSAR in Environmental Research - September 7, 2023 Category: Environmental Health Authors: K Takeda K Takeuchi Y Sakuratani K Kimbara Source Type: research