Phishing Target Identification Based on Neural Networks Using Category Features and Images

Table 4

The performance of models based on feature correlation results.

Models	Accuracy	Macro-F1 score	Weighted-F1 score
SVM	0.3717	0.0422	0.2557
LR	0.4119	0.1312	0.3487
KNN	0.6300	0.3544	0.6074
DT	0.8429	0.6614	0.8367
RF	0.8556	0.7306	0.8533
XGBoost	0.8796	0.7317	0.8722
LightGBM	0.8743	0.7120	0.8646

The bold values represent the best values of the evaluation metrics.