Table 5 Classification report with accuracy from experiment 2: Ensemble-based classifiers second dataset
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 | [[954 33] [31 1193]] | 0.941 |  − 1 1 | 0.97 0.97 | 0.97 0.97 | 0.97 0.97 | 985 1226 | 98.64 |
Adaboost classifier | [[898 89] [68 1156]] | 0.856 |  − 1 1 | 0.91 0.94 | 0.93 0.93 | 0.92 0.94 | 966 1245 | 94.21 |
Gradient boosting classifier | [[91671] [531171]] | 0.886 |  − 1 1 | 0.93 0.96 | 0.95 0.94 | 0.94 0.95 | 969 1242 | 96.47 |
Voting ensemble classifier | [[948 39] [631161]] | 0.907 |  − 1 1 | 0.96 0.95 | 0.94 0.97 | 0.95 0.96 | 1011 1200 | 97.19 |
Extra trees classifier | [[954 33] [291195]] | 0.943 |  − 1 1 | 0.97 0.98 | 0.97 0.97 | 0.97 0.97 | 983 1228 | 98.73 |
XGBoost classifier | [[948 39] [17 1207]] | 0.949 |  − 1 1 | 0.96 0.99 | 0.98 0.97 | 0.97 0.98 | 965 1246 | 98.37 |