Figure 1.

Feature selection using least absolute shrinkage and selection operator (LASSO) logistic regression. (a) Tuning parameter (λ) selection in the LASSO logistic regression performed using 10-fold cross-validation via the minimum criteria. The binomial deviance was plotted versus log(λ). Dotted vertical lines were drawn at the optimal λ based on the minimum criteria and 1 standard error for the minimum criteria, and the optimal λ was 0.0212. (b) The LASSO logistic regression algorithm was used to screen out 8 features with nonzero coefficients out of 20 features. A coefficient profile plot is produced versus the log(λ). LASSO: least absolute shrinkage and selection operator.