Identification of Potential Biomarkers and Immune Infiltration Characteristics in Ulcerative Colitis by Combining Results from Two Machine Learning Algorithms

Figure 5

(a) The LASSO regression model used 10-fold cross-validation and the minimum absolute shrinkage criterion to identify the optimal penalty coefficient . (b) Screening out feature genes by SVM-RFE algorithm. (c) Venn diagram of intersection feature genes between the LASSO regression model and SVM-RFE algorithm. (d) The expression levels of the four genes between UC group (red) and normal control group (blue) in the validation cohort. (e) ROC curve of the four feature genes in the discovery cohort. (f) ROC curve of the four feature genes in the validation cohort.

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