Incorporating biological prior knowledge for Bayesian learning via maximal knowledge-driven information priors

Boluki, Shahin; Esfahani, Mohammad Shahrokh; Qian, Xiaoning; Dougherty, Edward R

doi:10.1186/s12859-017-1893-4

BMC Bioinformatics

Table 4 Expected true error of different classification rules for the mammalian cell-cycle network. The constructed priors are considered using two precision factors: optimal precision factor (left) and estimated precision factor (right), with c=0.5, and c=0.6, where the minimum achievable error (Bayes error) is denoted by E r r _Bayes

From: Incorporating biological prior knowledge for Bayesian learning via maximal knowledge-driven information priors

(a) c=0.5, optimal precision factor, E r r _Bayes=0.2648						(b) c=0.5, estimated precision factor, E r r _Bayes=0.2648
Method/ n	30	60	90	120	150	Method/ n	30	60	90	120	150
Hist	0.3710	0.3423	0.3255	0.3155	0.3081	Hist	0.3710	0.3423	0.3255	0.3155	0.3081
CART	0.3326	0.3195	0.3057	0.3031	0.2975	CART	0.3326	0.3195	0.3057	0.3031	0.2975
RF	0.3359	0.3160	0.3015	0.2991	0.2933	RF	0.3359	0.3160	0.3015	0.2991	0.2933
SVM	0.3359	0.3112	0.2977	0.2959	0.2940	SVM	0.3359	0.3112	0.2977	0.2959	0.2940
Jeffreys’	0.3710	0.3423	0.3255	0.3155	0.3081	Jeffreys’	0.3710	0.3423	0.3255	0.3155	0.3081
RMEP	0.3236	0.3070	0.3010	0.2946	0.2910	RMEP	0.3315	0.3059	0.2985	0.2963	0.2930
RMDIP	0.3236	0.3070	0.3010	0.2946	0.2910	RMDIP	0.3314	0.3060	0.2986	0.2965	0.2931
REMLP	0.3425	0.3264	0.3146	0.3067	0.3011	REMLP	0.3488	0.3352	0.3202	0.3101	0.3048
MKDIP-E	0.3221	0.3070	0.3010	0.2949	0.2910	MKDIP-E	0.3313	0.3056	0.2982	0.2962	0.2929
MKDIP-D	0.3232	0.3070	0.3010	0.2952	0.2910	MKDIP-D	0.3315	0.3061	0.2986	0.2965	0.2931
MKDIP-R	0.3149	0.3028	0.2985	0.2943	0.2907	MKDIP-R	0.3205	0.3041	0.2969	0.2947	0.2919
(c) c=0.6, optimal precision factor, E r r _Bayes=0.31						(d) c=0.6, estimated precision factor, E r r _Bayes=0.31
Method/ n	30	60	90	120	150	Method/ n	30	60	90	120	150
Hist	0.3622	0.3608	0.3624	0.3641	0.3652	Hist	0.3622	0.3608	0.3624	0.3641	0.3652
CART	0.3554	0.3556	0.3507	0.3510	0.3447	CART	0.3554	0.3556	0.3507	0.3510	0.3447
RF	0.3524	0.3514	0.3467	0.3476	0.3420	RF	0.3524	0.3514	0.3467	0.3476	0.3420
SVM	0.3735	0.3684	0.3615	0.3602	0.3544	SVM	0.3735	0.3684	0.3615	0.3602	0.3544
Jeffreys’	0.3620	0.3559	0.3519	0.3502	0.3472	Jeffreys’	0.3620	0.3559	0.3519	0.3502	0.3472
RMEP	0.3415	0.3385	0.3394	0.3390	0.3386	RMEP	0.3528	0.3415	0.3407	0.3388	0.3378
RMDIP	0.3415	0.3383	0.3394	0.3390	0.3386	RMDIP	0.3529	0.3415	0.3408	0.3388	0.3378
REMLP	0.3666	0.3625	0.3587	0.3558	0.3530	REMLP	0.3700	0.3650	0.3603	0.3578	0.3546
MKDIP-E	0.3415	0.3384	0.3394	0.3390	0.3386	MKDIP-E	0.3525	0.3413	0.3405	0.3387	0.3377
MKDIP-D	0.3415	0.3386	0.3394	0.3390	0.3386	MKDIP-D	0.3532	0.3418	0.3409	0.3389	0.3379
MKDIP-R	0.3437	0.3409	0.3404	0.3401	0.3389	MKDIP-R	0.3486	0.3416	0.3416	0.3402	0.3387

The lowest error for each sample size is written in bold

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ISSN: 1471-2105

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