代码搜索：Inference
找到约 1,820 项符合「Inference」的源代码
代码结果 1,820
www.eeworm.com/read/318947/13465967
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/316944/13514000
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/150749/12267302
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/338238/12317184
h gibbs.h
#include "MonteCarlo.h"
#ifndef __GIBBS__
#define __GIBBS__
class Gibbs : public MonteCarlo {
/**
This class makes inference using Gibbs sampling method,
where in each step, only one no
www.eeworm.com/read/338238/12317194
h wolff.h
#include "MonteCarlo.h"
#include "PottsMRF.h"
#ifndef __WOLFF__
#define __WOLFF__
class Wolff : public MonteCarlo {
/**
This class makes inference using Wolff sampling method,
where in
www.eeworm.com/read/338238/12317258
cpp logmeanfield.cpp
#include "LogMeanField.h"
#include "MathFunctions.h"
#include
#include
double** LogMeanField::inference(int* converged) {
// define a threshold for convergence
double dBel = mf_
www.eeworm.com/read/119681/14824440
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/214923/15082919
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/344585/3207861
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay
www.eeworm.com/read/172172/9722059
m bay_modoutclass.m
function [Pplus, Pmin, bay,model] = bay_modoutClass(model,X,priorpos,type,nb,bay)
% Estimate the posterior class probabilities of a binary classifier using Bayesian inference
%
% >> [Ppos, Pneg] = bay