Journal of Big Data

Table 29 Mean performance of 7 classifiers in terms of AUC and F1-score on datasets with features from feature group all features A

From: Detecting cybersecurity attacks across different network features and learners

Classifier	All features A
Classifier	AUC	SD AUC	F1	SD F1
CatBoost	0.95602	0.00271	0.93653	0.002
Decision Tree	0.91190	0.00030	0.88740	0.000
LightGBM	0.95192	0.00616	0.92988	0.007
Naive Bayes	0.55359	0.00038	0.31448	0.000
Random Forest	0.95522	0.00474	0.93234	0.004
LightGBM	0.91324	0.00024	0.88905	0.000

Best metrics are highlighted in italics; SD AUC is the standard deviation of AUC and SD F1 is the standard deviation of the F1-score

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