From: A Bayesian method for comparing and combining binary classifiers in the absence of a gold standard
∼ 1000 positives | Sensitivity | Specificity | |||||
---|---|---|---|---|---|---|---|
2K-bit code | Combination | centerMean | Median | SD | Mean | Median | SD |
2 | C1∧C2∧C3 | 0.083 | 0.082 | 0.017 | 1.000 | 1.000 | 0.0000 |
4 | C2∧C3 | 0.098 | 0.097 | 0.018 | 1.000 | 1.000 | 0.0000 |
6 | C1∧C3 | 0.144 | 0.143 | 0.020 | 1.000 | 1.000 | 0.0000 |
18 | C1∧C2 | 0.483 | 0.481 | 0.053 | 1.000 | 1.000 | 0.0000 |
24 | At least two classifiers | 0.559 | 0.558 | 0.053 | 1.000 | 1.000 | 0.0000 |
64 | C2∨C3 | 0.645 | 0.647 | 0.047 | 0.997 | 0.997 | 0.0001 |
96 | C1∨C3 | 0.869 | 0.869 | 0.035 | 0.997 | 0.997 | 0.0001 |
120 | C1∨C2 | 0.932 | 0.933 | 0.021 | 0.998 | 0.998 | 0.0001 |
128‡ | C1∨C2∨C3 | 0.943 | 0.944 | 0.018 | 0.996 | 0.996 | 0.0002 |
∼ 5000 positives | Sensitivity | Specificity | |||||
2K-bit code | Combination | Mean | Median | SD | Mean | Median | SD |
2 | C1∧C2∧C3 | 0.065 | 0.066 | 0.007 | 1.000 | 1.000 | 0.0000 |
4 | C2∧C3 | 0.079 | 0.079 | 0.007 | 1.000 | 1.000 | 0.0000 |
6 | C1∧C3 | 0.123 | 0.123 | 0.008 | 1.000 | 1.000 | 0.0000 |
18 | C1∧C2 | 0.439 | 0.440 | 0.025 | 1.000 | 1.000 | 0.0000 |
24 | At least two classifiers | 0.510 | 0.511 | 0.026 | 1.000 | 1.000 | 0.0000 |
64 | C2∨C3 | 0.601 | 0.601 | 0.024 | 0.987 | 0.987 | 0.0002 |
96 | C1∨C3 | 0.850 | 0.852 | 0.018 | 0.991 | 0.991 | 0.0004 |
120 | C1∨C2 | 0.918 | 0.919 | 0.011 | 0.994 | 0.994 | 0.0004 |
128‡ | C1∨C2∨C3 | 0.930 | 0.931 | 0.010 | 0.986 | 0.986 | 0.0004 |