Table 5.
Regularized Logistic Regression | Support Vector Machine | Random Forest | Coded Diagnosis | |
---|---|---|---|---|
Health System 1 | ||||
Accuracy | 0.967 | 0.967 | 0.967 | 0.942 |
Recall | 0.962 | 0.942 | 1.000 | 0.962 |
Precision | 0.962 | 0.980 | 0.929 | 0.909 |
F1 score | 0.962 | 0.961 | 0.963 | 0.935 |
Health System 2 | ||||
Accuracy | 0.967 | 0.967 | 0.967 | 0.940 |
Recall | 0.985 | 0.985 | 0.985 | 0.985 |
Precision | 0.941 | 0.941 | 0.941 | 0.889 |
F1 score | 0.962 | 0.962 | 0.962 | 0.934 |
Health System 3 | ||||
Accuracy | 0.936 | 0.960 | 0.928 | 0.928 |
Recall | 0.910 | 0.955 | 0.925 | 0.940 |
Precision | 0.968 | 0.970 | 0.939 | 0.926 |
F1 score | 0.938 | 0.962 | 0.932 | 0.933 |
Health System 4 | ||||
Accuracy | 0.923 | 0.933 | 0.904 | 0.913 |
Recall | 0.951 | 1.000 | 1.000 | 0.951 |
Precision | 0.867 | 0.854 | 0.804 | 0.848 |
F1 score | 0.907 | 0.921 | 0.891 | 0.897 |