Table 5. Comparative performance of ML models with and without CO for SR prediction.

Dataset	Model	MAE	MSE	R 2
Dataset-1	LR	0.1523 ± 0.0037	0.0389 ± 0.0036	0.6162 ± 0.0167
	SVM	0.0826 ± 0.0115	0.0226 ± 0.0050	0.8163 ± 0.0565
	ANN	0.0593 ± 0.0023	0.0128 ± 0.0015	0.9023 ± 0.0129
	RF	0.0412 ± 0.0016	0.0095 ± 0.0007	0.9165 ± 0.0071
	CO-LR	0.1475 ± 0.0035	0.0382 ± 0.0018	0.6208 ± 0.0176
	CO-SVM	0.0729 ± 0.0118	0.0176 ± 0.0051	0.8337 ± 0.0576
	CO-ANN	0.0439 ± 0.0023	0.0106 ± 0.0015	0.9175 ± 0.0126
	CO-RF	0.0365 ± 0.0015	0.0074 ± 0.0007	0.9251 ± 0.0073
Dataset-2	LR	0.1105 ± 0.0072	0.0102 ± 0.0056	0.8936 ± 0.0165
	SVM	0.0762 ± 0.0069	0.0119 ± 0.0045	0.9510 ± 0.0163
	ANN	0.0745 ± 0.0059	0.0103 ± 0.0017	0.9571 ±0.0080
	RF	0.0469 ± 0.0031	0.0032 ± 0.0004	0.9868 ± 0.0018
	CO-LR	0.0927 ± 0.0069	0.0089 ± 0.0045	0.9093 ± 0.0163
	CO-SVM	0.0737 ± 0.0069	0.0119 ± 0.0045	0.9510 ± 0.0163
	CO-ANN	0.0745 ± 0.0059	0.0103 ± 0.0017	0.9571 ±0.0080
	CO-RF	0.0469 ± 0.0031	0.0032 ± 0.0004	0.9868 ± 0.0018