Fig. 3.

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) Variable selection in the LASSO model used 10-fold 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 8 nonzero coefficient variables. Abbreviations: LASSO, least absolute shrinkage and selection operator; SE, standard error.