Table 1 A confusion matrix showing the predication accuracy of the BBN model
Actual: positive | Scores | Actual: negative | Scores | Total | |
|---|---|---|---|---|---|
Predicted: positive | True positive (TP) | 38 | False positive (FP) | 2 | 40 |
Predicted: negative | False negative (FN) | 4 | True negative (TN) | 91 | 95 |
Total (test dataset) | 42 | 93 | 135 | ||
Model performance | Sensitivity (TP/TP + FN) | 0.90 | Specificity (TN/TN + FP) | 0.98 | |
Model error rate | 8.89% | ||||
Logarithmic loss | 0.3609 | ||||
Quadratic loss | 0.1619 | ||||
Spherical payoff | 0.9094 |