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Table 2 Influence of different \(\theta \) values on each index

From: Bayesian network structure learning with a new ensemble weights and edge constraints setting mechanism

\(\theta \)	0.10	0.20	0.30	0.40	0.50	0.60	0.70	0.80	0.90	1.00
F1-score	0.77	0.76	0.73	0.76	0.73	0.68	0.68	0.68	0.69	0.65
SHD	2.90	3.05	3.35	3.05	3.35	3.80	3.80	3.80	3.70	4.05
FDR	0.24	0.26	0.38	0.24	0.26	0.30	0.28	0.25	0.20	0.26

The bolded values represent the optimal values within the methods

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