Average test set sensitivity 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 | 0.43 (0.05) | 0.30 (0.08) | 0.32 (0.04) | 0.76 (0.02) | 0.47 (0.05) |
Blind—Naive Bayes | 0.44 (0.05) | 0.35 (0.09) | 0.38 (0.04) | 0.70 (0.02) | 0.37 (0.05) |
Blind—XGBoost | 0.37 (0.03) | 0.27 (0.08) | 0.30 (0.03) | 0.81 (0.03) | 0.56 (0.05) |
Blind—Random Forest | 0.31 (0.03) | 0.24 (0.07) | 0.25 (0.03) | 0.79 (0.04) | 0.58 (0.05) |
Separate—Logistic Regression | 0.69 (0.03) | 0.56 (0.09) | 0.63 (0.04) | 0.58 (0.02) | 0.16 (0.07) |
Separate—Naive Bayes | 0.60 (0.04) | 0.61 (0.11) | 0.57 (0.04) | 0.56 (0.03) | 0.13 (0.06) |
Separate—XGBoost | 0.67 (0.04) | 0.53 (0.12) | 0.57 (0.07) | 0.58 (0.02) | 0.19 (0.09) |
Separate—Random Forest | 0.71 (0.04) | 0.61 (0.12) | 0.67 (0.05) | 0.57 (0.03) | 0.20 (0.08) |
Equity—Logistic Regression | 0.58 (0.03) | 0.52 (0.09) | 0.63 (0.04) | 0.61 (0.02) | 0.14 (0.05) |
Equity—Naive Bayes | 0.56 (0.05) | 0.57 (0.09) | 0.63 (0.05) | 0.59 (0.03) | 0.12 (0.04) |
Equity—XGBoost | 0.55 (0.04) | 0.50 (0.10) | 0.69 (0.03) | 0.70 (0.02) | 0.24 (0.06) |
Equity—Random Forest | 0.65 (0.08) | 0.65 (0.11) | 0.72 (0.07) | 0.70 (0.06) | 0.13 (0.07) |
For each column and each resampling method, boldface indicates the top performing method(s).