On the development of an information system for monitoring user opinion and its role for the public

Journal of Big Data

Table 5 The classification metrics for the oversampled Russian texts

Classifier	NB	SVM	LR	k-NN	DT	RF	XGBoost	Average
Accuracy	0.71	0.60	0.84	0.67	0.91	0.95	0.64	0.76
Precision-macro	0.73	0.61	0.84	0.77	0.91	0.95	0.64	0.78
Precision-micro	0.71	0.60	0.84	0.67	0.91	0.95	0.64	0.76
Precision-weighted	0.73	0.61	0.84	0.77	0.91	0.95	0.64	0.78
Recall-macro	0.71	0.60	0.84	0.66	0.91	0.95	0.64	0.76
Recall-micro	0.71	0.60	0.84	0.67	0.91	0.95	0.64	0.76
Recall-weighted	0.71	0.60	0.84	0.67	0.91	0.95	0.64	0.76
F1-score-macro	0.71	0.59	0.84	0.65	0.90	0.95	0.63	0.75
F1-score-micro	0.71	0.60	0.84	0.67	0.91	0.95	0.64	0.76
F1-score-weighted	0.71	0.59	0.84	0.65	0.90	0.95	0.63	0.75
Average	0.71	0.60	0.84	0.69	0.91	0.95	0.64