Research Article
Construction of Artificial Intelligence Application Model for Supply Chain Financial Risk Assessment
Table 3
Comparison of different results.
| Algorithm | Accuracy | Recall | Precision | Specificity | G-means | F1-score | AUC |
| SVM | 87.21 | 96.76 | 88.27 | 47.05 | 92.44 | 92.3 | 71.95 | AdaBoost | 89.72 | 98.41 | 89.69 | 52.96 | 93.93 | 93.87 | 75.64 | PSO-SVM | 92.34 | 96.99 | 91.21 | 58.81 | 95.52 | 95.37 | 79.44 | DPSO-SVM | 93.57 | 96.02 | 92.52 | 64.73 | 96.18 | 96.14 | 82.33 | BP-AdaBoost | 94.90 | 98.38 | 95.34 | 76.46 | 96.87 | 96.82 | 87.46 | Ada-AMPSO-SVM | 96.13 | 98.02 | 95.29 | 82.37 | 97.61 | 97.62 | 91.16 |
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