代码搜索：bayesian

找到约 1,632 项符合「bayesian」的源代码

代码结果 1,632
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m trainmccpm.m

function [allStates lastState it updates iterTime G] = trainMCCPM(... G,samplesMat,updates,state,FP,saveFile) %%% use MCMC on our Bayesian, Hierarchical CPM %% I think it makes most sense to sam
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www.eeworm.com/read/289139/8573014

txt read_me.txt

Some brief notes ---------------- kfdemo.m is a Matlab script file to run a demonstration of the Bayesian Kalman filter. It loads file kfdemo.mat (saved as version 4 so that it will read in eit
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www.eeworm.com/read/428451/8867200

m bay_modoutclass.m

function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay) % Estimate the posterior class probabilities of a binary classifier using Bayesian inference % % >> [Ppos, Pneg] = bay
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www.eeworm.com/read/427586/8931948

m bay_modoutclass.m

function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay) % Estimate the posterior class probabilities of a binary classifier using Bayesian inference % % >> [Ppos, Pneg] = bay
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www.eeworm.com/read/183445/9158642

m bay_modoutclass.m

function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay) % Estimate the posterior class probabilities of a binary classifier using Bayesian inference % % >> [Ppos, Pneg] = bay
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www.eeworm.com/read/374698/9388836

m bay_modoutclass.m

function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay) % Estimate the posterior class probabilities of a binary classifier using Bayesian inference % % >> [Ppos, Pneg] = bay
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www.eeworm.com/read/177674/9442373

m demhmc3.m

%DEMHMC3 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/177674/9442497

m demhmc2.m

%DEMHMC2 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/177674/9442554

m hbayes.m

function [h, hdata] = hbayes(net, hdata) %HBAYES Evaluate Hessian of Bayesian error function for network. % % Description % H = HBAYES(NET, HDATA) takes a network data structure NET together % the da
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www.eeworm.com/read/177674/9442556

m gbayes.m

function [g, gdata, gprior] = gbayes(net, gdata) %GBAYES Evaluate gradient of Bayesian error function for network. % % Description % G = GBAYES(NET, GDATA) takes a network data structure NET together
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