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/317622/13500879
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/317622/13500888
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
www.eeworm.com/read/316604/13520400
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/316604/13520456
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/316604/13520465
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/140847/5779275
m bayesian_score_cpd.m
function score = bayesian_score_CPD(CPD, local_ev)
% bayesian_score_CPD Compute the Bayesian score of a tabular CPD using uniform Dirichlet prior
% score = bayesian_score_CPD(CPD, local_ev)
%
% The Ba
www.eeworm.com/read/133943/5897459
m bayesian_score_cpd.m
function score = bayesian_score_CPD(CPD, local_ev)
% bayesian_score_CPD Compute the Bayesian score of a tabular CPD using uniform Dirichlet prior
% score = bayesian_score_CPD(CPD, local_ev)
%
% The Ba
www.eeworm.com/read/359185/6352491
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/493206/6398469
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