Prediction for Traffic Accident Severity: Comparing the Bayesian Network and Regression Models

Table 3

Parameter learning results of the injury forecasting model.

	No.		1	2	3	4
Variables	Bti		1	1	2	2
	Vc		1	2	1	2
Estimation results	Noi = 0	Bayesian	0.1299	0.0907	0.2444	0.1813
		Test	0.1295	0.0906	0.2439	0.1812
		Absolute error	0.0004	0.0001	0.0005	0.0001
		Relative error	0.0031	0.0011	0.0020	0.0006
	1 ≤ Noi < 3	Bayesian	0.8552	0.8643	0.7293	0.7542
		Test	0.8561	0.8644	0.7317	0.7544
		Absolute error	0.0009	0.0001	0.0024	0.0002
		Relative error	0.0011	0.0001	0.0033	0.0003
	Noi ≥ 3	Bayesian	0.0150	0.0450	0.0263	0.0646
		Test	0.0144	0.0450	0.0244	0.0645
		Absolute error	0.0006	0.0000	0.0019	0.0001
		Relative error	0.04	0.0000	0.0722	0.0015
𝑁			1123