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The size of the generated confusion matrix using confusionmat function is not right, why?

Hello everyone,
I am working on a traffic sign recognition code in MATLAB using Belgian Traffic Sign Dataset.
The dataset consists of training data and test data (or evaluation data).
I resized the given images and extracted HOG features using the VL_HOG function from VL_feat library.
Then, I trained a multi class SVM using all of the signs inside the training dataset.
I used the fitcecoc function to obtain the classifier.
Upon training the multi-class SVM, I want to test the classifier performance using the test data and I used the predict and confusionmat functions.
There are 62 categories inside the training set (there are samples of 62 different traffic signs). However, the size of the returned confusion matrix is 53 by 53 instead of 62 by 62.
Why the size of the confusion matrix is not the same as the number of categories?

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1 Answer

Answer by Canberk Suat Gurel on 21 May 2018
 Accepted Answer

I found out that 9 of the folders in the testing dataset were empty, reducing the size of the confusion matrix to 53 by 53.

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