代码搜索：Probability
找到约 4,670 项符合「Probability」的源代码
代码结果 4,670
www.eeworm.com/read/253950/12173614
m gmmpost.m
function [post, a] = gmmpost(mix, x)
%GMMPOST Computes the class posterior probabilities of a Gaussian mixture model.
%
% Description
% This function computes the posteriors POST (i.e. the probability
www.eeworm.com/read/339665/12211607
m gmmprob.m
function prob = gmmprob(mix, x)
%GMMPROB Computes the data probability for a Gaussian mixture model.
%
% Description
% This function computes the unconditional data density P(X) for a
% Gaussian mixt
www.eeworm.com/read/339665/12211629
m gmmpost.m
function [post, a] = gmmpost(mix, x)
%GMMPOST Computes the class posterior probabilities of a Gaussian mixture model.
%
% Description
% This function computes the posteriors POST (i.e. the probability
www.eeworm.com/read/150905/12250482
m gmmprob.m
function prob = gmmprob(mix, x)
%GMMPROB Computes the data probability for a Gaussian mixture model.
%
% Description
% This function computes the unconditional data density P(X) for a
% Gaussian mixt
www.eeworm.com/read/150905/12250494
m gmmpost.m
function [post, a] = gmmpost(mix, x)
%GMMPOST Computes the class posterior probabilities of a Gaussian mixture model.
%
% Description
% This function computes the posteriors POST (i.e. the probability
www.eeworm.com/read/252928/12254320
m multinonunifmutation.m
function [parent] = multiNonUnifMutation(parent,bounds,Ops)
% Multi-Non uniform mutation changes all of the parameters of the parent
% based on a non-uniform probability distribution. This Gaussian
%
www.eeworm.com/read/252916/12254767
m multinonunifmutation.m
function [parent] = multiNonUnifMutation(parent,bounds,Ops)
% Multi-Non uniform mutation changes all of the parameters of the parent
% based on a non-uniform probability distribution. This Gaussian
%
www.eeworm.com/read/150760/12266168
m pdfgmm.m
function y = pdfgmm(X, model )
% PDFGMM Evaluates gaussian mixture model.
%
% Synopsis:
% y = pdfgmm(X, model )
%
% Description:
% This function evaluates a probability density function
% determin
www.eeworm.com/read/150760/12266178
m contents.m
% Probability distribution estimation.
%
% emgmm - Expectation-Maximization Algorithm for GMM.
% melgmm - Maximizes Expectation of Log-Likelihood for Gaussian mixture.
% mlcgmm - Maximal Li
www.eeworm.com/read/150760/12266197
m~ contents.m~
% Probability distribution estimation.
%
% emgmm - Expectation-Maximization Algorithm for GMM.
% melgmm - Maximizes Expectation of Log-Likelihood for Gaussian mixture.
% mlcgmm - Maximal Li