Table 2 Algorithmic predictions from 7214 defendants.

Logistic regression with 7 features (A) (LR7), logistic regression with 2 features (B) (LR2), a nonlinear SVM with 7 features (C) (NL-SVM), and the commercial COMPAS software with 137 features (D) (COMPAS). The results in columns (A), (B), and (C) correspond to the average testing accuracy over 1000 random 80%/20% training/testing splits. The values in the square brackets correspond to the 95% bootstrapped [columns (A), (B), and (C)] and binomial [column (D)] confidence intervals.

(A) LR7(B) LR2(C) NL-SVM(D) COMPAS
Accuracy (overall)66.6% [64.4, 68.9]66.8% [64.3, 69.2]65.2% [63.0, 67.2]65.4% [64.3, 66.5]
Accuracy (black)66.7% [63.6, 69.6]66.7% [63.5, 69.2]64.3% [61.1, 67.7]63.8% [62.2, 65.4]
Accuracy (white)66.0% [62.6, 69.6]66.4% [62.6, 70.1]65.3% [61.4, 69.0]67.0% [65.1, 68.9]
False positive (black)42.9% [37.7, 48.0]45.6% [39.9, 51.1]31.6% [26.4, 36.7]44.8% [42.7, 46.9]
False positive (white)25.3% [20.1, 30.2]25.3% [20.6, 30.5]20.5% [16.1, 25.0]23.5% [20.7, 26.5]
False negative (black)24.2% [20.1, 28.2]21.6% [17.5, 25.9]39.6% [34.2, 45.0]28.0% [25.7, 30.3]
False negative (white)47.3% [40.8, 54.0]46.1% [40.0, 52.7]56.6% [50.3, 63.5]47.7% [45.2, 50.2]