Figure 2 | Scientific Reports

Figure 2

From: Evaluating machine learning classifiers for glaucoma referral decision support in primary care settings

Figure 2

Permutation feature importance applied to each classifier: (a) Logistic regression, (b) Support vector machine, and (c) Adaptive boosting (AdaBoost). Mean decrease in F1 score is shown for each feature: age, systolic and diastolic blood pressure, gender (male), body mass index (BMI), intraocular pressure (IOP) in the right eye (RE) and left eye (LE), age-related macular degeneration (AMD) category, race (black, Hispanic, Asian, and other), and presence of diabetes and arthritis.

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