Table 6 Classification report with accuracy from experiment 3: Ensemble-based classifiers on the merged dataset without cross-validation
From: Phishing website prediction using base and ensemble classifier techniques with cross-validation
Classifier used | Confusion matrix | Kappa score (k) | Phishing (− 1) or non-phishing (1) | Precision | Recall | F1-score | Support | Accuracy achieved (%) |
|---|---|---|---|---|---|---|---|---|
Bagging classifier | [[1211 44] [37 1411]] | 0.948 |  − 1 1 | 0.96 0.97 | 0.97 0.97 | 0.97 0.97 | 1248 1455 | 89.03 |
Adaboost classifier | [[891 364] [275 1173]] | 0.523 |  − 1 1 | 0.71 0.81 | 0.76 0.76 | 0.74 0.79 | 1166 1537 | 67.41 |
Gradient boosting classifier | [[1158 97] [74 1374]] | 0.873 |  − 1 1 | 0.92 0.95 | 0.94 0.93 | 0.93 0.94 | 1232 1471 | 88.70 |
Voting ensemble classifier | [[1176 79] [65 1383]] | 0.893 |  − 1 1 | 0.94 0.96 | 0.95 0.95 | 0.94 0.95 | 1241 1462 | 84.98 |
Extra trees classifier | [[1214 41] [35 1413]] | 0.943 |  − 1 1 | 0.97 0.98 | 0.97 0.97 | 0.97 0.97 | 1249 1454 | 87.37 |
XGBoost classifier | [[1207 48] [34 1414]] | 0.939 |  − 1 1 | 0.96 0.98 | 0.97 0.97 | 0.97 0.97 | 1241 1462 | 88.71 |