Table 4 Precision, recall and F1 scores of naive bayes, logistic regression, support vector machine, decision tree, random forest, and muti-layer perceptron machine learning models
Models | Class | Precision (%) | Recall (%) | F1-Score (%) |
|---|---|---|---|---|
Naive Bayes | Low Risk | 28 | 94 | 43 |
Moderate Risk | 47 | 4 | 7 | |
High Risk | 62 | 8 | 15 | |
Logistic Regression | Low Risk | 44 | 26 | 32 |
Moderate Risk | 47 | 64 | 54 | |
High Risk | 53 | 45 | 49 | |
Support Vector Machine | Low Risk | 94 | 71 | 81 |
Moderate Risk | 74 | 96 | 84 | |
High Risk | 98 | 79 | 87 | |
Decision Tree | Low Risk | 78 | 77 | 77 |
Moderate Risk | 83 | 84 | 83 | |
High Risk | 85 | 84 | 85 | |
Random Forest | Low Risk | 88 | 79 | 83 |
Moderate Risk | 87 | 90 | 88 | |
High Risk | 85 | 90 | 87 | |
Muti-Layer Perceptron | Low Risk | 97 | 93 | 95 |
Moderate Risk | 94 | 97 | 95 | |
High Risk | 98 | 97 | 97 |