代码搜索：bayesian

找到约 1,632 项符合「bayesian」的源代码

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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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1 mailinspect.1

\" t .TH MAILINSPECT 1 "Bayesian Text Classification Tools" "Version 1.3" "" .SH NAME mailinspect \- sort an mbox by category and pipe emails to a command. .SH SYNOPSIS .HP .B mailinspect [-zjiI] -c
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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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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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www.eeworm.com/read/430506/1929401

m bayesdemo3.m

% BAYESDEMO3 Bayesian risk and minimax strategy. % % Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac % (c) Czech Technical University Prague, http://cmp.felk.cvut.cz %
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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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