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/493206/6398532
m bayesian_belief_networks.m
function [decision, P] = Bayesian_Belief_Networks(net, data)
% Find the most likely decision given a Bayesian belief network and data for the decision
%
% Inputs:
% net - A bayesian belief n
www.eeworm.com/read/493206/6398541
m bayesian_parameter_est.m
function [mu, sigma] = Bayesian_parameter_est(train_features, train_targets, sigma, region)
% Estimate the mean using the Bayesian parameter estimation for Gaussian mixture algorithm
% Inputs:
%
www.eeworm.com/read/477893/6725313
ppt issues in bayesian networks.ppt
www.eeworm.com/read/410924/11264784
m bayesian_model_comparison.m
function D = Bayesian_Model_Comparison(train_features, train_targets, Ngaussians, region)
% Classify using the Bayesian model comparison algorithm. This function accepts as inputs
% the maximum nu
www.eeworm.com/read/410924/11264928
m bayesian_belief_networks.m
function [decision, P] = Bayesian_Belief_Networks(net, data)
% Find the most likely decision given a Bayesian belief network and data for the decision
%
% Inputs:
% net - A bayesian belief n
www.eeworm.com/read/410924/11264945
m bayesian_parameter_est.m
function [mu, sigma] = Bayesian_parameter_est(train_features, train_targets, sigma, region)
% Estimate the mean using the Bayesian parameter estimation for Gaussian mixture algorithm
% Inputs:
%
www.eeworm.com/read/405077/11472101
pdf bayesian compressive sensing.pdf
www.eeworm.com/read/405069/11472171
m bayesian_model_comparison.m
function test_targets = Bayesian_Model_Comparison(train_patterns, train_targets, test_patterns, Ngaussians)
% Classify using the Bayesian model comparison algorithm. This function accepts as inputs
www.eeworm.com/read/405069/11472227
m bayesian_belief_networks.m
function [decision, P] = Bayesian_Belief_Networks(net, data)
% Find the most likely decision given a Bayesian belief network and data for the decision
%
% Inputs:
% net - A bayesian belief n
www.eeworm.com/read/405069/11472236
m bayesian_parameter_est.m
function [mu, sigma] = Bayesian_parameter_est(train_patterns, train_targets, sigma)
% Estimate the mean using the Bayesian parameter estimation for Gaussian mixture algorithm
% Inputs:
% pattern