Medical Image Classification Utilizing Ensemble Learning and Levy Flight-Based Honey Badger Algorithm on 6G-Enabled Internet of Things

Table 2

Classification results (%) of each feature selection optimization algorithm on the CXR dataset.

Optimizer	Model	Accuracy	Balanced accuracy	F1-score	Recall	Precision
GWO	DenseNet	82.69	77.86	81.60	82.69	84.48
	MobileNet	85.74	81.24	84.89	85.74	87.89
	Ensemble model	86.06	81.58	85.23	86.06	88.27
WOA	DenseNet	81.25	75.85	79.84	81.25	83.53
	MobileNet	84.78	79.96	83.77	84.78	87.22
	Ensemble model	85.10	80.47	84.17	85.10	87.28
FFA	DenseNet	81.57	76.28	80.22	81.57	83.77
	MobileNet	85.26	80.60	84.33	85.26	87.55
	Ensemble model	84.94	80.17	83.96	84.94	87.33
HGS	DenseNet	82.85	77.99	81.76	82.85	84.74
	MobileNet	85.58	80.94	84.67	85.58	87.94
	Ensemble model	86.22	81.79	85.41	86.22	88.38
AOA	DenseNet	82.21	77.14	80.99	82.21	84.25
	MobileNet	85.90	81.37	85.04	85.90	88.16
	Ensemble model	84.94	80.26	83.99	84.94	87.17
AO	DenseNet	82.21	76.97	80.91	82.21	84.57
	MobileNet	84.62	79.91	83.65	84.62	86.78
	Ensemble model	86.22	81.97	85.47	86.22	88.09
HBA	DenseNet	83.01	78.03	81.87	83.01	85.16
	MobileNet	86.06	81.75	85.28	86.06	87.97
	Ensemble model	86.06	81.75	85.28	86.06	87.97
LFHBA	DenseNet	83.65	78.97	82.66	83.65	85.49
	MobileNet	86.54	82.22	85.78	86.54	88.61
	Ensemble model	87.10	82.82	86.19	87.10	88.56