LogCAD: An Efficient and Robust Model for Log-Based Conformal Anomaly Detection

Table 7

Effectiveness of multiple models on BGL_100K log data set.

Injection rate (%)	Classifier	Accuracy	Precision	Recall	F1	MCC
5	CP-AB-LR	0.78	0.864	0.76	0.809	0.648
	CP-AB-SVM	0.805	0.87	0.8	0.833	0.676
	CP-AB-NB	0.756	0.857	0.72	0.783	0.622
	LogCAD	0.854	0.806	1	0.893	0.71
10	CP-AB-LR	0.756	0.888	0.8	0.8	0.613
	CP-AB-SVM	0.683	0.75	0.72	0.735	0.55
	CP-AB-NB	0.78	0.786	0.88	0.83	0.624
	LogCAD	0.854	0.806	1	0.893	0.71
15	CP-AB-LR	0.732	0.85	0.68	0.756	0.598
	CP-AB-SVM	0.829	0.909	0.8	0.851	0.709
	CP-AB-NB	0.756	0.857	0.72	0.783	0.622
	LogCAD	0.829	0.909	0.8	0.851	0.709
20	CP-AB-LR	0.732	0.792	0.76	0.776	0.592
	CP-AB-SVM	0.756	0.8	0.8	0.8	0.613
	CP-AB-NB	0.683	0.75	0.72	0.735	0.55
	LogCAD	0.756	0.8	0.8	0.8	0.613