代码搜索：Stepwise
找到约 97 项符合「Stepwise」的源代码
代码结果 97
www.eeworm.com/read/316604/13520507
m sohc.m
function [features, targets, label] = SOHC(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inpu
www.eeworm.com/read/359185/6352574
m sohc.m
function [features, targets, label] = SOHC(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inpu
www.eeworm.com/read/493206/6398584
m sohc.m
function [features, targets, label] = SOHC(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inpu
www.eeworm.com/read/410924/11265029
m sohc.m
function [features, targets, label] = SOHC(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inpu
www.eeworm.com/read/405069/11472292
m sohc.m
function [patterns, targets, label] = SOHC(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inputs:
% t
www.eeworm.com/read/131588/14136392
m sohc.m
function [features, targets, label] = SOHC(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inpu
www.eeworm.com/read/129915/14217772
m sohc.m
function [features, targets, label] = SOHC(train_features, train_targets, Nmu, region, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inpu
www.eeworm.com/read/472943/1402606
m msnvenofig10.m
% Figure 10: Ratio of median Forward Stepwise MSE to the median oracle MSE.
% The number of variables is fixed at 200, the number of observations at 100,
% ie. delta=n/p=.5, and the median was taken
www.eeworm.com/read/386597/2570203
m sohc.m
function [patterns, targets, label] = SOHC(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inputs:
% t
www.eeworm.com/read/474600/6813549
m sohc.m
function [patterns, targets, label] = SOHC(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using the stepwise optimal hierarchical clustering algorithm
%Inputs:
% t