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The glucose is an important source of fuel for the body. The binding affinity is an essential indicator of the interaction of a glucose molecule with its binder. This paper proposes a novel machine learning model for predicting the binding affinity of a small glucose molecule with the binder. Seven regression algorithms were compared on a dataset is generated based on Molecular Mechanics-Generalized Born and Surface Area (MM-GBSA). Through the comparison, Random Forest and Decision Tree weredoi:10.18280/ria.330309 fatcat:6kiyhjpfizdnziijdaepi442ju