代码搜索：gdata
找到约 456 项符合「gdata」的源代码
代码结果 456
www.eeworm.com/read/220289/14843828
m gbayes.m
function [g, gdata, gprior] = gbayes(net, gdata)
%GBAYES Evaluate gradient of Bayesian error function for network.
%
% Description
% G = GBAYES(NET, GDATA) takes a network data structure NET together
www.eeworm.com/read/220289/14843901
m rbfgrad.m
function [g, gdata, gprior] = rbfgrad(net, x, t)
%RBFGRAD Evaluate gradient of error function for RBF network.
%
% Description
% G = RBFGRAD(NET, X, T) takes a network data structure NET together
% wi
www.eeworm.com/read/212307/15160136
m gbayes.m
function [g, gdata, gprior] = gbayes(net, gdata)
%GBAYES Evaluate gradient of Bayesian error function for network.
%
% Description
% G = GBAYES(NET, GDATA) takes a network data structure NET together
www.eeworm.com/read/212307/15160200
m rbfgrad.m
function [g, gdata, gprior] = rbfgrad(net, x, t)
%RBFGRAD Evaluate gradient of error function for RBF network.
%
% Description
% G = RBFGRAD(NET, X, T) takes a network data structure NET together
% wi
www.eeworm.com/read/170936/9779293
m gbayes.m
function [g, gdata, gprior] = gbayes(net, gdata)
%GBAYES Evaluate gradient of Bayesian error function for network.
%
% Description
% G = GBAYES(NET, GDATA) takes a network data structure NET together
www.eeworm.com/read/170936/9779390
m rbfgrad.m
function [g, gdata, gprior] = rbfgrad(net, x, t)
%RBFGRAD Evaluate gradient of error function for RBF network.
%
% Description
% G = RBFGRAD(NET, X, T) takes a network data structure NET together
% wi
www.eeworm.com/read/367152/9779885
m group.m
% group - Gather/sort same class data and indexes them
%
% [gdata,gindex,nclass]= group(ldata[,sortit])
%
% _____OUTPUT_____________________________________________________________
% gdata grouped &
www.eeworm.com/read/367152/9780153
m lda.m
% lda - Linear Discriminant Analysis (batch)
%
% [pldata,pvar,paxis] = lda(ldata[,options])
%
% _____OUTPUTS____________________________________________________________
% pldata projected labeled dat
www.eeworm.com/read/415313/11076561
m gbayes.m
function [g, gdata, gprior] = gbayes(net, gdata)
%GBAYES Evaluate gradient of Bayesian error function for network.
%
% Description
% G = GBAYES(NET, GDATA) takes a network data structure NET together
www.eeworm.com/read/415313/11076709
m rbfgrad.m
function [g, gdata, gprior] = rbfgrad(net, x, t)
%RBFGRAD Evaluate gradient of error function for RBF network.
%
% Description
% G = RBFGRAD(NET, X, T) takes a network data structure NET together
% wi