Using Machine Learning to predict substituent effects reaserch plan
by Shane Leonard and Robert Mawhinney
Published onMay 18, 2022
Using Machine Learning to predict substituent effects reaserch plan
In this research I am attempting to use machine learning algorithms to predict substituent effects on silicate-polyol complex formations. The machine algorithm will first be tested using the effects of substituents in isodesmic reactions and the chirality of tetra-substituted methane's. The type of machine learning to be used is still undecided though the current thinking is using a neural network with either a simple linear regression or a Naive Bayes model
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