Journal of Big Data

Table 16 Time complexity of ML models in IDS

From: Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction

SI. No.	ML model	Time complexity
1	DT (Decision Trees)	\(O(n \cdot m \cdot \log (m))\)
2	RF (Random Forests)	\(O(t \cdot n \cdot m \cdot log(m))\)
3	ET (Extra Trees)	\(O(t \cdot n \cdot m \cdot log(m))\)
4	XGB (XGBoost)	\(O(t \cdot d)\)

Back to article page