The Treebagger give different results in 2012a and 2013a

I used
B = TreeBagger(NTrees(j),train_feats',train_labels');
and
Y = predict(B,test_feats');
to classification, in train_feats each column is a sample,the train_labels total of 30 categories,label from 0 to 29.
when I run the code in matlab 2012a the accuracy almost 90%,but when i update to 2013a the accuracy is less than 1%. The data and the code are intact, why the result is so different?
Does anyone have an explanation?

 Accepted Answer

This might be the explanation, and it includes a suggestion of how to avoid the problem:
http://www.mathworks.com/support/bugreports/927692

1 Comment

Thank you so much for your answer and advice. The answer is exactly the problem. I change the labels from ordinals to chars:
NewLabels{i} = num2str(labels(i));
problem solved!
Thank you again for your help.

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More Answers (0)

Asked:

xq
on 19 Apr 2013

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