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

Table 3

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

Optimizer	Model	Accuracy	Balanced accuracy	F1-score	Recall	Precision
GWO	DenseNet	85.85	85.85	85.35	85.85	89.05
	MobileNet	88.12	88.12	87.78	88.12	90.74
	Ensemble model	93.49	93.49	93.45	93.49	94.28
MFO	DenseNet	86.67	86.67	86.38	86.67	89.45
	MobileNet	88.53	88.53	88.25	88.53	91.00
	Ensemble model	93.80	93.80	93.78	93.80	94.55
WOA	DenseNet	87.19	87.19	86.86	87.19	89.84
	MobileNet	88.43	88.43	88.15	88.43	90.79
	Ensemble model	93.39	93.39	93.35	93.39	94.26
FFA	DenseNet	86.26	86.26	85.88	86.26	89.46
	MobileNet	88.33	88.33	87.99	88.33	90.57
	Ensemble model	87.19	87.19	86.87	87.19	89.78
HGS	DenseNet	87.19	87.19	86.87	87.19	89.78
	MobileNet	88.33	88.33	88.02	88.33	90.87
	Ensemble model	93.29	93.29	93.26	93.29	94.19
AOA	DenseNet	86.98	86.98	86.65	86.98	89.66
	MobileNet	88.74	88.74	88.49	88.74	91.08
	Ensemble model	93.70	93.70	93.68	93.70	94.48
AO	DenseNet	87.40	87.40	87.03	87.40	89.95
	MobileNet	88.43	88.43	88.13	88.43	90.98
	Ensemble model	93.80	93.80	93.78	93.80	94.55
HBA	DenseNet	87.50	87.50	87.17	87.50	90.01
	MobileNet	88.43	88.43	88.18	88.43	90.85
	Ensemble model	93.80	93.80	93.78	93.80	94.55
LFHBA	DenseNet	87.71	87.71	87.44	87.71	90.30
	MobileNet	88.95	88.95	88.66	88.95	91.19
	Ensemble model	94.32	94.32	94.30	94.32	94.93