<p>(a) and (b) shows the number of false predictions and number of included variables over different alpha values using cross-validated elastic net regularized logistic regression, respectively. Generally, a larger alpha value yields stronger regularization, and thus involves less variables for the regression model. Note that the blue dashed curves represent the regression results using EHSCHV variables, while the green solid curves use the variables derived from labeling. (c) presents a hyper-plane using support vector machine to separate the two groups of patients with distinct technical outcomes by the two remaining labeling-derived variables of an exploratory regression model built upon all observations.</p
