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. 2023 Feb 23;14:1007624. doi: 10.3389/fimmu.2023.1007624

Figure 6.

Figure 6

Screening of core genes and validation based on machine learning methods in RA and MDD. (A) Coefficient profiles of variables in the LASSO regression model in RA. (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model in RA. (C) The optimum root mean squared error (RMSE) of SVM-based method based on 44 characteristic genes in RA. (D) Coefficient profiles of variables in the LASSO regression model in MDD. (E) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model in MDD. (F) The optimum root mean squared error (RMSE) of SVM-based method based on 27 characteristic genes in MDD. (G) 14 core genes in RA and 14 core genes in MDD screened by LASSO regression model and SVM-based method, and 6 common core genes were obtained after taking the intersection.