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Fig. 4 | Journal of Translational Medicine

Fig. 4

From: Development and validation of a clinic machine-learning nomogram for the prediction of risk stratifications of prostate cancer based on functional subsets of peripheral lymphocyte

Fig. 4

Lasso regression to generate the selected clinic features with iterative fitting using 5-fold cross-validation. Variation of the hyperparameter λ in Lasso regression is plotted vs. MSE (mean-squared-error) (A) and the coefficient profiles of clinic features (B). The light-blue vertical lines in (A) were drawn at the optimal values with one standard-deviation criteria. The vertical dashed line was drawn at the value selected at the logarithmic scale (λ), and nine features with non-zero coefficients are indicated

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