Fig. 2

Features selection using the LASSO binary logistic regression model. (a) Log (Lambda) value of the 16 features in the LASSO model. A coefficient profile plot was produced against the log (lambda) sequence. (b) Parameter selection in the LASSO model used tenfold cross-validation via minimum criterion. Partial likelihood deviation (binomial deviation) curves and logarithmic (lambda) curves were plotted. Use the minimum standard and 1se (1-SE standard) of the minimum standard to draw a vertical dashed line at the optimal value. The optimal lambda produced four nonzero coefficients. Abbreviations: LASSO: Least Absolute Shrinkage and Selection Operator; SE, Standard Error.