代码搜索：Approximation
找到约 1,542 项符合「Approximation」的源代码
代码结果 1,542
www.eeworm.com/read/140847/5779545
m bethe_free_energy.m
function loglik = bethe_free_energy(engine, evidence)
% BETHE_FREE_ENERGY Compute Bethe free energy approximation to the log likelihood
% loglik = bethe_free_energy(engine, evidence)
%
% The Bethe fre
www.eeworm.com/read/133943/5897727
m bethe_free_energy.m
function loglik = bethe_free_energy(engine, evidence)
% BETHE_FREE_ENERGY Compute Bethe free energy approximation to the log likelihood
% loglik = bethe_free_energy(engine, evidence)
%
% The Bethe fre
www.eeworm.com/read/492033/6430582
h plelemqq.h
#ifndef PLELEMQQ_H
#define PLELEMQQ_H
#include "alias.h"
struct matrix;
struct vector;
struct ivector;
/**
class planeelemqq defines plane quadrilateral element with
bi-quadratic approximation
www.eeworm.com/read/485544/6552645
m evidence.m
function [net, gamma, logev] = evidence(net, x, t, num)
%EVIDENCE Re-estimate hyperparameters using evidence approximation.
%
% Description
% [NET] = EVIDENCE(NET, X, T) re-estimates the hyperparamete
www.eeworm.com/read/253950/12173305
m evidence.m
function [net, gamma, logev] = evidence(net, x, t, num)
%EVIDENCE Re-estimate hyperparameters using evidence approximation.
%
% Description
% [NET] = EVIDENCE(NET, X, T) re-estimates the hyperparamete
www.eeworm.com/read/339665/12211190
m evidence.m
function [net, gamma, logev] = evidence(net, x, t, num)
%EVIDENCE Re-estimate hyperparameters using evidence approximation.
%
% Description
% [NET] = EVIDENCE(NET, X, T) re-estimates the hyperparamete
www.eeworm.com/read/150905/12249868
m evidence.m
function [net, gamma, logev] = evidence(net, x, t, num)
%EVIDENCE Re-estimate hyperparameters using evidence approximation.
%
% Description
% [NET] = EVIDENCE(NET, X, T) re-estimates the hyperparamete
www.eeworm.com/read/150749/12267206
m trainlssvm.m
function [model,b,X,Y] = trainlssvm(model,X,Y)
% Train the support values and the bias term of an LS-SVM for classification or function approximation
%
% >> [alpha, b] = trainlssvm({X,Y,type,gam,ke
www.eeworm.com/read/150749/12267339
m trainlssvm.m
function [model,b,X,Y] = trainlssvm(model,X,Y)
% Train the support values and the bias term of an LS-SVM for classification or function approximation
%
% >> [alpha, b] = trainlssvm({X,Y,type,gam,ke
www.eeworm.com/read/251851/12315337
m stretch_func_fmincon.m
function [f,g] = ...
stretch_func_fmincon(X,sys_eq,ode_param,n_vector)
% Compute objective function for the optimization problem in the flow pipe
% segment approximation procedure for `nonlin