Figure 5
From: Development of risk models of incident hypertension using machine learning on the HUNT study data
(a) Coefficient sizes in least absolute shrinkage and selection operator (LASSO) regression fitted on the training set with increasing regularization. Only the 10 last features to be zeroed out are shown. (b) The performance of the LASSO regression model on the test set as regularization was increased. Curves are shown as pointwise mean curves with red shaded 95% confidence interval calculated by bootstrapping. AUC area under the receiver-operator curve, BMI body mass index, BP blood pressure, Chol cholesterol, Fam. hist. of hyp. family history of hypertension, HDL high-density lipid, ICI integrated calibration index. Log natural logarithm, PAI physical activity indicator.
