Table 3

Average test set specificity with SD (at training set specificity of approximately 0.76) of different combinations of resampling procedure plus statistical/machine learning method, by racial/ethnic group

	Asian	Black	Hispanic	White	Size of range
Blind—Logistic Regression	0.91 (0.01)	0.93 (0.01)	0.94 (0.01)	0.57 (0.01)	0.38 (0.01)
Blind—Naive Bayes	0.91 (0.01)	0.90 (0.01)	0.91 (0.00)	0.61 (0.01)	0.30 (0.01)
Blind—XGBoost	0.96 (0.00)	0.95 (0.01)	0.95 (0.00)	0.54 (0.02)	0.42 (0.02)
Blind—Random Forest	0.97 (0.00)	0.96 (0.00)	0.96 (0.00)	0.52 (0.04)	0.45 (0.04)
Separate—Logistic Regression	0.66 (0.01)	0.66 (0.02)	0.74 (0.01)	0.75 (0.00)	0.10 (0.01)
Separate—Naive Bayes	0.72 (0.03)	0.63 (0.08)	0.78 (0.01)	0.74 (0.01)	0.15 (0.07)
Separate—XGBoost	0.71 (0.02)	0.73 (0.06)	0.76 (0.05)	0.77 (0.01)	0.10 (0.04)
Separate—Random Forest	0.61 (0.03)	0.64 (0.03)	0.70 (0.03)	0.75 (0.02)	0.15 (0.04)
Equity—Logistic Regression	0.79 (0.01)	0.78 (0.01)	0.76 (0.01)	0.71 (0.01)	0.08 (0.01)
Equity—Naive Bayes	0.81 (0.01)	0.74 (0.01)	0.76 (0.02)	0.71 (0.02)	0.10 (0.01)
Equity—XGBoost	0.81 (0.01)	0.80 (0.02)	0.72 (0.01)	0.65 (0.01)	0.17 (0.01)
Equity—Random Forest	0.70 (0.06)	0.65 (0.03)	0.66 (0.04)	0.61 (0.06)	0.10 (0.02)

For each column and each resampling method, boldface indicates the top performing method(s).