代码搜索：DSLVQ
找到约 25 项符合「DSLVQ」的源代码
代码结果 25
www.eeworm.com/read/191902/8417246
m dslvq.m
function [features, targets, w] = DSLVQ(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% t
www.eeworm.com/read/286662/8751859
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
www.eeworm.com/read/177129/9468906
m dslvq.m
function [features, targets, w] = DSLVQ(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% t
www.eeworm.com/read/372113/9521241
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
www.eeworm.com/read/362008/10023920
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
www.eeworm.com/read/357874/10199134
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
www.eeworm.com/read/349842/10796835
m dslvq.m
function [features, targets, w] = DSLVQ(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% t
www.eeworm.com/read/399996/7816866
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
www.eeworm.com/read/397106/8067690
m dslvq.m
function [features, targets, w] = DSLVQ(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using linear vector quantization
%Inputs:
% train_features - Input f
www.eeworm.com/read/397099/8068898
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat