Table 10.

Classification results of machine learning models using GloVe with SMOTE.

Models	Accuracy	Precision	Recall	F1 score
RF	0.73	0.73	0.73	0.73
AB	0.58	0.58	0.58	0.58
ET	0.75	0.75	0.75	0.75
LR	0.60	0.59	0.60	0.59
MLP	0.65	0.67	0.65	0.69
GBM	0.63	0.63	0.63	0.63
kNN	0.64	0.64	0.64	0.63
ER-VC	0.73	0.73	0.73	0.73

RF: Random Forest; LR: Logistic Regression; MLP: Multilayer Perceptron; GBM: Gradient Boosting Machine; AB: AdaBoost, kNN: k Nearest Neighbours; ET: Extra Tree Classifier; GloVe: Global Vectors; SMOTE: Synthetic Minority Oversampling Approach; ER-VC: Extreme Regression-Voting Classifier.