Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning

Journal of Big Data

Table 6 FS vs. FE for binary classification with 9 features

Models	Accuracy (%)	Precision (%)	Re-call (%)	F1-score (%)	MCC	FS (s)	Training (s)	Inference (ms)
Feature selection
DT	80.73	79.50	77.74	78.44	0.5721	8.38	0.22	12.11
RF	79.07	78.53	74.55	75.73	0.5293		7.56	801.32
kNN	77.44	82.90	69.38	70.66	0.5050		1.09	709,996.65
NB	78.99	82.82	71.94	73.58	0.5366		*0.11*	12.50
MLP	80.73	79.50	77.74	78.44	0.5721		37.3	136.17
Feature extraction
DT	*86.54*	*85.12*	*86.33*	*85.62*	*0.7128*	*5.27*	1.44	*8.10*
RF	86.45	85.02	86.30	85.54	0.7127		18.61	838.21
kNN	71.00	76.33	76.79	70.99	0.3409		1.55	10,172.81
NB	83.35	81.76	82.68	82.15	0.6443		0.13	18.52
MLP	86.30	84.85	86.26	85.41	0.7111		81.58	139.20