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SAMPLE and TRAINING must have the same number of columns. after using pca

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sun rise
sun rise 2022-1-31
load featurs_T
load featurs_S
load Group_Train
load Group_Test
%{
cv_x=cov(Feat1);
[V,D] = eig(cv_x);
d=diag(D);
d=d(end:-1:1);
sm_d=cumsum(d) /sum(d);
idx=find(sm_d>0.99);
T=[V(:,end:-1:idx(1))]';
new_feat1=T*Feat1';
%TrainingSet= new_feat1';
new_feat2=T*Feat2';
%TestSet= new_feat2';
TrainingSet = new_feat1';
TestSet = new_feat2';
%}
Feat1= Feat1';
Feat2= Feat2';
Group_Train1 = Group_Train1';
Group_Test1 = Group_Test1';
%}
Feat1 = pca(Feat1);
Feat2 = pca (Feat2);
%------------------------
%}
% result1= multisvm(TrainingSet,Group_Train1,TestSet,Group_Test1);
result= classify(Feat2,Feat1,Group_Train1,'diaglinear');
%testresult = result1;
Accuracy = mean(Group_Test1==result) * 100;
fprintf('Accuracy = %.2f\n', Accuracy);
fprintf('error rate = %.2f\n ', mean(result ~= Group_Test1 ) * 100);
Error using classify (line 153)
SAMPLE and TRAINING must have the same number of columns.
Error in HOG2 (line 32)
result= classify(Feat2,Feat1,Group_Train1,'diaglinear');
After using pca the matrix dimensions change
Feat1= 1032*1032
Feat2 =109*109
result = 1032*1

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R2019a

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