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/445694/7591873
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/445694/7591882
m multifloatnonunifmutation.m
function [parent] = multiFloatNonUnifMutation(parent,bounds,Ops)
% Multi-Non uniform mutation changes all of the parameters of the parent
% based on a non-uniform probability distribution. This Gauss
www.eeworm.com/read/444595/7611126
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/440025/7695699
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/436736/7762984
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/250359/7811458
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/299459/7850884
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/299459/7850900
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/299459/7850917
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/298649/7947002
m multinon.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