Table 14.

Classification results of proposed ER-VC model for binary classification.

Feature	Acc.	Class	Prec.	Rec.	F1
BoW	0.96	Survived	0.97	0.96	0.97
		Not-survived	0.96	0.97	0.96
		Weighted avg	0.96	0.96	0.96
TF-IDF	0.98	Survived	0.98	0.98	0.98
		Not-survived	0.98	0.98	0.98
		Weighted avg	0.98	0.98	0.98
GloVe	0.91	Survived	0.93	0.89	0.91
		Not-survived	0.89	0.93	0.91
		Weighted avg	0.91	0.91	0.91

GloVe: Global Vectors; ER-VC: Extreme Regression-Voting Classifier; TF-IDF: Term Frequency-Inverse Document Frequency; BoW: Bag of Words.