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. 2021 Mar 19;11:644933. doi: 10.3389/fonc.2021.644933

Figure 2.

Figure 2

Feature selection using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model. (A) Tuning parameter (Lambda) selection in the LASSO model used 10-fold cross-validation via minimum criteria. The gray line in the figure is the partial likelihood estimate corresponding to the optimal value of lambda. The optimal lambda value of 1.638236e-05 was chosen. (B) LASSO coefficient profiles of the 114 features. A vertical line was plotted at the optimal lambda value, which resulted in ten features with non-zero coefficients.