Table 3 Performance evaluations of...

Table 3

Performance evaluations of different models for the test data set

Cutting environment	Response	Method	Statistical metrics
Cutting environment	Response	Method	MAPE	MaxAPE	MAE	NRMSE	R²
MQL	F_RMQL	PR	1.5	3.3	20.33	0.098	0.9955
		SVR	0.9	1.8	13.00	0.055	0.9983
		GPR	0.9	2.4	12.05	0.056	0.9985
		ANN	0.7	1.2	9.89	0.044	0.9992
	P_cMQL	PR	2.7	9.5	0.142	0.065	0.9983
		SVR	0.9	1.7	0.057	0.024	0.9997
		GPR	0.9	2.7	0.053	0.023	0.9998
		ANN	0.8	2.4	0.047	0.022	0.9999
	K_sMQL	PR	1.4	2.8	28.63	0.375	0.9906
		SVR	1.1	2.2	23.99	0.339	0.9601
		GPR	0.9	2.9	19.41	0.315	0.9750
		ANN	0.8	2.3	16.96	0.265	0.9799
HPC	F_RHPC	PR	1.3	2.4	19.11	0.076	0.9981
		SVR	0.8	2.2	11.78	0.053	0.9991
		GPR	0.7	1.8	10.89	0.048	0.9992
		ANN	0.6	1.4	9.89	0.043	0.9992
	P_cHPC	PR	2.1	6.7	0.126	0.053	0.9992
		SVR	0.9	2.7	0.065	0.032	0.9995
		GPR	0.7	2.7	0.054	0.030	0.9996
		ANN	0.6	1.3	0.043	0.018	0.9999
	K_sHPC	PR	1.4	3.1	28.51	0.470	0.9464
		SVR	0.8	2.0	16.13	0.300	0.9713
		GPR	0.8	2.3	15.86	0.265	0.9678
		ANN	0.7	2.3	13.51	0.245	0.9739

Cutting environment	Response	Method	Statistical metrics
Cutting environment	Response	Method	MAPE	MaxAPE	MAE	NRMSE	R²
MQL	F_RMQL	PR	1.5	3.3	20.33	0.098	0.9955
		SVR	0.9	1.8	13.00	0.055	0.9983
		GPR	0.9	2.4	12.05	0.056	0.9985
		ANN	0.7	1.2	9.89	0.044	0.9992
	P_cMQL	PR	2.7	9.5	0.142	0.065	0.9983
		SVR	0.9	1.7	0.057	0.024	0.9997
		GPR	0.9	2.7	0.053	0.023	0.9998
		ANN	0.8	2.4	0.047	0.022	0.9999
	K_sMQL	PR	1.4	2.8	28.63	0.375	0.9906
		SVR	1.1	2.2	23.99	0.339	0.9601
		GPR	0.9	2.9	19.41	0.315	0.9750
		ANN	0.8	2.3	16.96	0.265	0.9799
HPC	F_RHPC	PR	1.3	2.4	19.11	0.076	0.9981
		SVR	0.8	2.2	11.78	0.053	0.9991
		GPR	0.7	1.8	10.89	0.048	0.9992
		ANN	0.6	1.4	9.89	0.043	0.9992
	P_cHPC	PR	2.1	6.7	0.126	0.053	0.9992
		SVR	0.9	2.7	0.065	0.032	0.9995
		GPR	0.7	2.7	0.054	0.030	0.9996
		ANN	0.6	1.3	0.043	0.018	0.9999
	K_sHPC	PR	1.4	3.1	28.51	0.470	0.9464
		SVR	0.8	2.0	16.13	0.300	0.9713
		GPR	0.8	2.3	15.86	0.265	0.9678
		ANN	0.7	2.3	13.51	0.245	0.9739

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