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LDAELMradbas.m
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%%
clear all
clc
load A.mat
load index.mat
SL=2; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(2)
%%
clear all
clc
load A.mat
load index.mat
SL=3; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(3)
%%
clear all
clc
load A.mat
load index.mat
SL=4; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(4)
%%
clear all
clc
load A.mat
load index.mat
SL=5; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(5)
%%
clear all
clc
load A.mat
load index.mat
SL=6; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(6)
%%
clear all
clc
load A.mat
load index.mat
SL=7; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(7)
%%
clear all
clc
load A.mat
load index.mat
SL=8; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(8)
%%
clear all
clc
load A.mat
load index.mat
SL=9; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(9)
%%
clear all
clc
load A.mat
load index.mat
SL=10; %从板
Source=A{1,1};
Target=A{1,SL};
Source_label=(vec2ind(index{1,1}))';
Target_label=(vec2ind(index{1,SL}))';
%归一化
Source=Source./repmat(sqrt(sum(Source.^2,1)),size(Source,1),1);
Target=Target./repmat(sqrt(sum(Target.^2,1)),size(Target,1),1);
%% 使用LDA进行数据降维
options = [];
options.Regu=1;
options.Fisherface = 1;
[eigvector, eigvalue] = LDA(Source_label,options,Source);
input_train=Source*eigvector;
input_test=Target*eigvector;
for cishu=1:10
clear max;
clear result;
%% ELM
error2=0;
counter=0;
class_num=[1;5;10;15;20];
ActivationFunction='radbas';
for t=1:5
Hnumbt=class_num(t,1);
for v=0:20
counter=counter+1;
Cv=10^v;
try
[TrainingAccuracy, TestingAccuracy] = fast_elm(input_train,Source_label,input_test,Target_label,1, Hnumbt, ActivationFunction,Cv);
catch
error2 = error2 +1;
TestingAccuracy =0;
end
testaccracy=TestingAccuracy;
result(counter,1)=Hnumbt;
result(counter,2)=v;
result(counter,3)=TestingAccuracy;
end
end
[max,index]=max(result(:,3));
maxpara=result(index,:);
newresult(cishu,:)=maxpara;
end
save LDAelm_radbas(10)