代码搜索：Bayesian

找到约 1,632 项符合「Bayesian」的源代码

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www.eeworm.com/read/174377/9590035

hpp models.hpp

#ifndef _BAYES_FILTER__MODELS #define _BAYES_FILTER__MODELS /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and conditions
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hpp unsflt.hpp

#ifndef _BAYES_FILTER_UNSCENTED #define _BAYES_FILTER_UNSCENTED /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and condit
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hpp indirect.hpp

#ifndef _BAYES_FILTER_INDIRECT #define _BAYES_FILTER_INDIRECT /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and conditio
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hpp bayesflt.hpp

#ifndef _BAYES_FILTER #define _BAYES_FILTER /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and conditions of use. * * $
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hpp bayesexception.hpp

#ifndef _BAYES_FILTER_EXCEPTION #define _BAYES_FILTER_EXCEPTION /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and condit
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hpp covflt.hpp

#ifndef _BAYES_FILTER_COVARIANCE #define _BAYES_FILTER_COVARIANCE /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and cond
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hpp itrflt.hpp

#ifndef _BAYES_FILTER_ITERATED_COVARIANCE #define _BAYES_FILTER_ITERATED_COVARIANCE /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm
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hpp infflt.hpp

#ifndef _BAYES_FILTER_INFORMATION #define _BAYES_FILTER_INFORMATION /* * Bayes++ the Bayesian Filtering Library * Copyright (c) 2002 Michael Stevens * See accompanying Bayes++.htm for terms and co
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www.eeworm.com/read/170936/9779255

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 wit
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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 wit
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