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 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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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/396844/2406679

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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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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m demev2.m

%DEMEV2 Demonstrate Bayesian classification for the MLP. % % Description % A synthetic two class two-dimensional dataset X is sampled from a % mixture of four Gaussians. Each class is associated
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m fevbayes.m

function [extra, invhess] = fevbayes(net, y, a, x, t, x_test, invhess) %FEVBAYES Evaluate Bayesian regularisation for network forward propagation. % % Description % EXTRA = FEVBAYES(NET, Y, A, X,
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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 % t
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www.eeworm.com/read/359369/2978479

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 toget
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www.eeworm.com/read/473227/6849358

cpp kalmanslam.cpp

/* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2004 Michael Stevens * See accompanying Bayes++.htm for terms and conditions of use. * * $Header: /cvsroot/bayesclasses/Bayes++/SLAM/ka
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hpp slam.hpp

/* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2004 Michael Stevens * See accompanying Bayes++.htm for terms and conditions of use. * * $Header: /cvsroot/bayesclasses/Bayes++/SLAM/SL
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