Accuracy Calculation using confusionmat?

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shawin
shawin on 23 Oct 2020
Edited: shawin on 23 Oct 2020
Kindly I have an issue with accuracy calculation, please could you help ?
y_train = [ 1 1 1 4 4 3 3 5 5 5 ]; % for x_train
%x_test : has no true labels.
predictedLabel=[ 1 2 3 4 5 ]; %predicted lables for x_test
I used the code below :
group=y_train ; % 10
grouphat=predictedLabel; % for test 5 test data
C=confusionmat(group,grouphat);
Accuracy = sum ( diag (C)) / sum (C (:)) ×100;
but get error:
Error using confusionmat (line 75)
G and GHAT need to have same number of rows
I had error since the test data is more or less than the train ( no lables)?
No true label for test data ( semi supervised learning )
Thank you

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