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Table 2 Performance (precision, recall, F1) and fairness (demographic parity and equalised odds) measures for the different models

From: Fair automated assessment of noncompliance in cargo ship networks

Measure

Baseline

Random forest

Fair random forest

precision (non-white)

97.1%

89.8%

89.0%

precision (white)

95.2%

87.7%

86.1%

recall (non-white)

42.3%

75.5%

82.5%

recall (white)

5.2%

88.6%

86.6%

F1 (non-white)

58.9%

82.0%

85.6%

F1 (white)

9.9%

88.2%

86.4%

\(\epsilon_{\text{parity}}\)

0.317

0.099

0.023

\(\epsilon_{\text{odds}}\)

0.371

0.132

0.040

AUCY

0.543 ± 0.006

0.814 ± 0.004

0.776 ± 0.008

AUCS

0.672 ± 0.010

0.627 ± 0.014

0.538 ± 0.011