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 5 Expected true error of different classification rules for the TP53 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=0.3146						(b) c=0.5, estimated precision factor, E r r _Bayes=0.3146
Method/ n	15	30	45	60	75	Method/ n	15	30	45	60	75
Hist	0.3586	0.3439	0.3337	0.3321	0.3296	Hist	0.3586	0.3439	0.3337	0.3321	0.3296
CART	0.3633	0.3492	0.3350	0.3314	0.3295	CART	0.3633	0.3492	0.3350	0.3314	0.3295
RF	0.3791	0.3574	0.3461	0.3400	0.3362	RF	0.3791	0.3574	0.3461	0.3400	0.3362
SVM	0.3902	0.3481	0.3433	0.3324	0.3322	SVM	0.3902	0.3481	0.3433	0.3324	0.3322
Jeffreys’	0.3809	0.3439	0.3457	0.3321	0.3334	Jeffreys’	0.3809	0.3439	0.3457	0.3321	0.3334
RMEP	0.3399	0.3392	0.3360	0.3315	0.3328	RMEP	0.3791	0.3489	0.3377	0.3329	0.3302
RMDIP	0.3399	0.3392	0.3360	0.3315	0.3328	RMDIP	0.3789	0.3490	0.3378	0.3329	0.3302
REMLP	0.3405	0.3340	0.3320	0.3292	0.3287	REMLP	0.3417	0.3372	0.3350	0.3318	0.3292
MKDIP-E	0.3397	0.3398	0.3351	0.3306	0.3297	MKDIP-E	0.3675	0.3470	0.3373	0.3326	0.3298
MKDIP-D	0.3397	0.3398	0.3347	0.3306	0.3297	MKDIP-D	0.3668	0.3472	0.3374	0.3327	0.3298
MKDIP-R	0.3435	0.3354	0.3321	0.3295	0.3283	MKDIP-R	0.3471	0.3402	0.3349	0.3316	0.3287
(c) c=0.6, optimal precision factor, E r r _Bayes=0.2691						(d) c=0.6, estimated precision factor, E r r _Bayes=0.2691
Method/ n	15	30	45	60	75	Method/ n	15	30	45	60	75
Hist	0.3081	0.2965	0.2906	0.2883	0.2846	Hist	0.3081	0.2965	0.2906	0.2883	0.2846
CART	0.3173	0.2988	0.2882	0.2846	0.2796	CART	0.3173	0.2988	0.2882	0.2846	0.2796
RF	0.3333	0.3035	0.2946	0.2850	0.2842	RF	0.3333	0.3035	0.2946	0.2850	0.2842
SVM	0.3322	0.3091	0.2991	0.2926	0.2857	SVM	0.3322	0.3091	0.2991	0.2926	0.2857
Jeffreys’	0.3105	0.2936	0.2860	0.2828	0.2819	Jeffreys’	0.3105	0.2936	0.2860	0.2828	0.2819
RMEP	0.2924	0.2922	0.2847	0.2843	0.2835	RMEP	0.3346	0.3024	0.2894	0.2860	0.2823
RMDIP	0.2924	0.2922	0.2847	0.2843	0.2835	RMDIP	0.3344	0.3023	0.2895	0.2858	0.2823
REMLP	0.3003	0.2908	0.2869	0.2839	0.2832	REMLP	0.3054	0.2930	0.2910	0.2870	0.2850
MKDIP-E	0.2924	0.2909	0.2837	0.2851	0.2837	MKDIP-E	0.3341	0.3025	0.2898	0.2864	0.2822
MKDIP-D	0.2924	0.2909	0.2837	0.2851	0.2837	MKDIP-D	0.3347	0.3024	0.2898	0.2862	0.2822
MKDIP-R	0.3032	0.2917	0.2868	0.2843	0.2825	MKDIP-R	0.3096	0.2981	0.2910	0.2869	0.2849

The lowest error for each sample size is written in bold

Back to article page

ISSN: 1471-2105

Contact us

General enquiries: journalsubmissions@springernature.com