代码搜索：Bayesian
找到约 1,632 项符合「Bayesian」的源代码
代码结果 1,632
www.eeworm.com/read/292964/3937194
m update_params_complete.m
function CPD = update_params_complete(CPD, self_ev, pev)
% UPDATE_PARAMS_COMPLETE Bayesian parameter updating given completely observed data (root_gaussian)
% CPD = update_params_complete(CPD, self_ev
www.eeworm.com/read/434858/1868132
m update_params_complete.m
function CPD = update_params_complete(CPD, self_ev, pev)
% UPDATE_PARAMS_COMPLETE Bayesian parameter updating given completely observed data (root_gaussian)
% CPD = update_params_complete(CPD, self_ev
www.eeworm.com/read/396844/2406985
m update_params_complete.m
function CPD = update_params_complete(CPD, self_ev, pev)
% UPDATE_PARAMS_COMPLETE Bayesian parameter updating given completely observed data (root_gaussian)
% CPD = update_params_complete(CPD, self_ev
www.eeworm.com/read/393163/2488141
m update_params_complete.m
function CPD = update_params_complete(CPD, self_ev, pev)
% UPDATE_PARAMS_COMPLETE Bayesian parameter updating given completely observed data (root_gaussian)
% CPD = update_params_complete(CPD, self_ev
www.eeworm.com/read/385191/2594694
svn-base learn_struct_gs2.m.svn-base
function [dag, best_score, cache] = learn_struct_gs2(data, nodesizes, seeddag, varargin)
%
% LEARN_STRUCT_GS2(data,seeddag) learns a structure of Bayesian net by Greedy Search.
% dag = learn_struct_gs
www.eeworm.com/read/172172/9722112
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/367440/9748480
m bay_rr.m
function [A,B,C,D,E,F,G] = bay_rr(X,Y,gam,level,nb,eigvals,eigvec)
% Bayesian inference of the cost on the three levels of linear ridge regression
%
% >> cost = bay_rr(X, Y, gam, level)
%
% This fun
www.eeworm.com/read/428451/8867318
m bay_lssvm.m
function [A,B,C,D,E] = bay_lssvm(model,level,type, nb, bay)
% Compute the posterior cost for the 3 levels in Bayesian inference
%
% >> cost = bay_lssvm({X,Y,type,gam,sig2}, level, type)
% >> cost = b
www.eeworm.com/read/427586/8932180
m bay_lssvm.m
function [A,B,C,D,E] = bay_lssvm(model,level,type, nb, bay)
% Compute the posterior cost for the 3 levels in Bayesian inference
%
% >> cost = bay_lssvm({X,Y,type,gam,sig2}, level, type)
% >> cost = b
www.eeworm.com/read/184950/9064002
m bayesmean.m
function y = bayesmean(mu, sigma, mu0, sigma0, N, x)
% y = bayesmean(mu, sigma, mu0, sigma0, N, x)
%
% Bayesian learning of the mean of a Gaussian with known variance.
% N samples are drawn