Learning genetic epistasis using Bayesian network scoring criteria

BMC Bioinformatics

Table 3 Recall for scoring criteria

	Scoring Criterion	200	400	800	1600	Total
1	score _{α = 162}	5259	6043	6566	6890	24758
2	score _AIC ₂	5204	5969	6511	6849	24533
3	score _AIC ₁	5186	5960	6481	6830	24457
4	score _{α = 54}	5223	5941	6473	6813	24450
5	score _K ₂	5303	5962	6371	6747	24383
6	score _{α = 42}	5203	5902	6425	6794	24324
7	score _{α = 36}	5181	5866	6395	6768	24210
8	score _{α = 30}	5147	5816	6352	6754	24069
9	score _{α = 24}	5080	5767	6300	6725	23872
10	score _{α = 21}	5031	5733	6265	6704	23733
11	score _MDR	4870	5710	6324	6748	23652
12	score _{α = 18}	4973	5681	6230	6681	23565
13	score _{α = 15}	4902	5622	6183	6647	23354
14	score _Epi ₁	4984	5529	6105	6575	23193
15	score _{α = 12}	4786	5531	6119	6605	23041
16	score _{α = 9}	4649	5416	6026	6547	22638
17	score _{α = 6}	4383	5219	5901	6453	21956
18	score _MML ₁	4151	5159	5903	6473	21686
19	score _MML ₂	3881	4969	5780	6412	21042
20	score _Epi ₂	3895	4901	5715	6329	20840
21	score _{α = 3}	3953	4862	5652	6285	20752
22	score _Suz ₁	3618	4696	5595	6251	20160
23	score _Suz ₂	2500	3712	4811	5737	17760

The sum of the recall for each scoring criterion over 7000 data sets for sample sizes of 200, 400, 800, and 1600. The last column gives the total recall over all sample sizes. The scoring criteria are listed in descending order of total recall.

ISSN: 1471-2105