Table 3 Metrics obtained from the training data set classifier.
From: Using machine learning to predict student outcomes for early intervention and formative assessment
Assessment criteria | Random forest | SVM | C5.0 | CART |
|---|---|---|---|---|
Accuracy (%) | 76.62% | 73.11% | 81.06% | 81.67% |
Number of correctly classified samples | 375 | 359 | 398 | 401 |
Number of misclassified samples | 115 | 132 | 93 | 90 |
TP rate | 0.766 | 0.731 | 0.810 | 0.816 |
FP rate | 0.233 | 0.289 | 0.286 | 0.184 |
Precision | 0.720 | 0,717 | 0,731 | 0.751 |
Recall | 0.843 | 0.833 | 0.718 | 0.812 |
F-Score | 0.776 | 0.754 | 0.724 | 0.780 |
Kappa value | 0.423 | 0.401 | 0.569 | 0.623 |
