Table 2.

Mean error (ME), mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and R² values assessing performance of machine learning regression methods based on Demirjian and Cameriere method, respectively.

Method	ML model	ME	MAE	MSE	RMSE	R2
Demirjian	Traditional	−0.647	0.982	22.254	4.717	–
	BRR	−0.002	0.510	0.404	0.636	0.928
	DT	0.011	0.523	0.609	0.780	0.892
	KNN	−0.027	0.517	0.435	0.660	0.923
Cameriere	Traditional	0.592	0.846	0.755	0.869	–
	BRR	−0.030	0.535	0.436	0.660	0.923
	DT	0.052	0.584	0.601	0.775	0.893
	KNN	−0.015	0.473	0.340	0.583	0.940