Effect of Molecular Descriptors on the Development of Machine Learning Models for the Prediction of Yield Sooting Index

) is close to 1.0, and the mean absolute error is less than 20 between the experimental data and prediction data for the training, valid, and test sets, respectively. Among the developed ML models, the GB model, by using the PFI-filtered mordred computed descriptors, exhibits the best performance. The present work is valuable for the selection of descriptors for the development of ML models to predict fuel properties.