From: Empirical evaluation of scoring functions for Bayesian network model selection
 |  |  | Greedy Hill Climbing | Optimal | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
GoldNet | Size | Score | Add | Delete | Rev | Mis | Total | Add | Delete | Rev | Mis | Total |
Austr | 200 | AIC | 16 | 14 | 1 | 1 | 32 | 11 | 6 | 2 | 2 | 21 |
 | 200 | MDL | 9 | 17 | 0 | 0 | 26 | 0 | 8 | 1 | 4 | 13 |
 | 200 | fNML | 11 | 16 | 0 | 1 | 28 | 20 | 7 | 0 | 4 | 31 |
 | 200 | 0.1 | 7 | 17 | 0 | 1 | 25 | 0 | 10 | 0 | 4 | 14 |
 | 200 | 0.5 | 9 | 17 | 0 | 0 | 26 | 1 | 9 | 1 | 3 | 14 |
 | 200 | 1 | 9 | 17 | 0 | 0 | 26 | 1 | 9 | 1 | 3 | 14 |
 | 200 | 5 | 11 | 12 | 2 | 2 | 27 | 5 | 6 | 1 | 6 | 18 |
 | 200 | 10 | 14 | 14 | 0 | 2 | 30 | 8 | 7 | 2 | 4 | 21 |
 | 600 | AIC | 18 | 15 | 1 | 0 | 34 | 7 | 1 | 0 | 0 | 8 |
 | 600 | MDL | 13 | 15 | 1 | 0 | 29 | 0 | 2 | 0 | 0 | 2 |
 | 600 | fNML | 13 | 15 | 2 | 0 | 30 | 1 | 3 | 0 | 7 | 11 |
 | 600 | 0.1 | 11 | 15 | 1 | 1 | 28 | 0 | 4 | 0 | 1 | 5 |
 | 600 | 0.5 | 12 | 15 | 1 | 1 | 29 | 0 | 3 | 0 | 1 | 4 |
 | 600 | 1 | 12 | 15 | 1 | 1 | 29 | 0 | 3 | 0 | 1 | 4 |
 | 600 | 5 | 14 | 14 | 1 | 4 | 33 | 1 | 2 | 0 | 0 | 3 |
 | 600 | 10 | 15 | 15 | 0 | 3 | 33 | 4 | 3 | 1 | 9 | 17 |
 | 1000 | AIC | 18 | 13 | 1 | 0 | 32 | 7 | 0 | 1 | 0 | 8 |
 | 1000 | MDL | 15 | 15 | 1 | 0 | 31 | 0 | 0 | 0 | 0 | 0 |
 | 1000 | fNML | 16 | 15 | 0 | 3 | 34 | 2 | 1 | 1 | 8 | 12 |
 | 1000 | 0.1 | 15 | 15 | 1 | 0 | 31 | 0 | 0 | 0 | 0 | 0 |
 | 1000 | 0.5 | 15 | 15 | 1 | 0 | 31 | 0 | 0 | 0 | 0 | 0 |
 | 1000 | 1 | 15 | 15 | 1 | 0 | 31 | 0 | 0 | 0 | 0 | 0 |
 | 1000 | 5 | 17 | 15 | 2 | 1 | 35 | 2 | 0 | 4 | 6 | 12 |
 | 1000 | 10 | 18 | 15 | 2 | 1 | 36 | 4 | 1 | 1 | 8 | 14 |
Crx | 200 | AIC | 20 | 14 | 0 | 2 | 36 | 9 | 2 | 4 | 3 | 18 |
 | 200 | MDL | 9 | 16 | 0 | 3 | 28 | 1 | 8 | 0 | 9 | 18 |
 | 200 | fNML | 16 | 15 | 1 | 1 | 33 | 19 | 5 | 6 | 4 | 34 |
 | 200 | 0.1 | 6 | 16 | 0 | 3 | 25 | 1 | 11 | 0 | 6 | 18 |
 | 200 | 0.5 | 10 | 16 | 0 | 3 | 29 | 1 | 8 | 0 | 9 | 18 |
 | 200 | 1 | 9 | 15 | 0 | 4 | 28 | 1 | 7 | 0 | 10 | 18 |
 | 200 | 5 | 13 | 14 | 1 | 2 | 30 | 5 | 6 | 3 | 5 | 19 |
 | 200 | 10 | 19 | 14 | 2 | 0 | 35 | 9 | 4 | 3 | 3 | 19 |
 | 600 | AIC | 21 | 14 | 0 | 0 | 35 | 8 | 1 | 2 | 0 | 11 |
 | 600 | MDL | 14 | 16 | 0 | 0 | 30 | 1 | 3 | 1 | 0 | 5 |
 | 600 | fNML | 14 | 14 | 0 | 4 | 32 | 3 | 3 | 1 | 7 | 14 |
 | 600 | 0.1 | 11 | 15 | 0 | 1 | 27 | 2 | 6 | 2 | 1 | 11 |
 | 600 | 0.5 | 13 | 15 | 0 | 0 | 28 | 1 | 3 | 1 | 0 | 5 |
 | 600 | 1 | 13 | 15 | 0 | 0 | 28 | 1 | 3 | 1 | 0 | 5 |
 | 600 | 5 | 17 | 13 | 2 | 3 | 35 | 6 | 2 | 2 | 7 | 17 |
 | 600 | 10 | 18 | 13 | 0 | 3 | 34 | 8 | 3 | 2 | 6 | 19 |
 | 1000 | AIC | 21 | 15 | 0 | 0 | 36 | 7 | 1 | 1 | 0 | 9 |
 | 1000 | MDL | 14 | 15 | 1 | 0 | 30 | 1 | 2 | 1 | 1 | 5 |
 | 1000 | fNML | 17 | 15 | 0 | 4 | 36 | 2 | 2 | 0 | 9 | 13 |
 | 1000 | 0.1 | 14 | 15 | 0 | 0 | 29 | 1 | 3 | 1 | 1 | 6 |
 | 1000 | 0.5 | 13 | 15 | 0 | 0 | 28 | 1 | 3 | 1 | 1 | 6 |
 | 1000 | 1 | 13 | 15 | 0 | 0 | 28 | 1 | 3 | 1 | 1 | 6 |
 | 1000 | 5 | 17 | 15 | 0 | 0 | 32 | 4 | 2 | 0 | 11 | 17 |
 | 1000 | 10 | 18 | 14 | 2 | 4 | 38 | 6 | 2 | 1 | 8 | 17 |