Fig. 3

Development of LASSO models. a Selecting the optimal number of features based on minimum criteria in the training set. b Based on the optimal λ value of 0.036 with log(λ) = − 3.315, eight features were selected. c Selecting the optimal number of features based on minimum criteria in the SMOTE-training set. d Based on the optimal λ value of 0.008 with log(λ) = − 4.785, nine features were selected. LASSO: least absolute shrinkage and selection operator; SMOTE: synthetic minority over-sampling technique