01 January 2022>: Clinical ResearchJia-shan Pan AE* , Yi-ding Chen BC* , Han-dong Ding B , Tian-chi Lan B , Fei Zhang B , Jin-biao Zhong A* , Gui-yi Liao AF*
Med Sci Monit 2022; 28:e933559
Figure 3 Demographics and clinical feature selection using the LASSO binary regression model.(A) LASSO coefficient profiles for 30 features. Each coefficient profile was plotted against the logarithm of the lambda parameter. The vertical line was drawn at the value selected using 5-fold cross-validation, where the optimal lambda value resulted in 22 features with nonzero coefficients. (B) Optimal lambda parameter selection in the LASSO model using 5-fold cross-validation via minimum criteria. The curve of the partial likelihood deviance (binomial deviance) was plotted versus the logarithm of the lambda parameter. Dotted vertical lines were drawn at the optimal values by using the minimum criteria and the I-SE of the minimum criteria (the I-SE criteria). The figures use the R software (version 4.0.3; https://www.R-project.org). LASSO – least absolute shrinkage and selection operator; SE – standard error.