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One-Class SVM yielding different results with OpenMP in Matlab #151
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Hello, I try to reproduce by your files but I get parallelAccuracy=0.5 in Matlab. Could you please provide the decision values in both normal and parallel cases? |
Sure! Here are the stored Some system-information: |
Sorry, maybe I didn't make myself clear. For decision values, I mean:
(you can see it in matlab/README) When I run your code, I get the same |
In addition, I did check your provided models and found they look good. But since you said you only applied OpenMP in prediction, I think it's normal that we can get the same models. If there is something wrong, it may happen on |
Oh, I'm sorry, I misunderstood! |
Hello, Your decision values in parallel seem abnormal. Since we cannot reproduce your case, it's hard to make a conclusion where is wrong. We recommend you to substitute C for Matlab to avoid other influences. If your result still seems weird, we are pleased to discuss with you. |
I see very weird behavior when applying OpenMP as stated in the FAQ, in combination with one-class-SVMs.
When I train a one-class SVM with OpenMP in Matlab, I get a different accuracy (way better) than when I train the one-class SVM without OpenMP. However, when using Octave, I get the same results in both cases.
Accuracy-Results(Matlab):
Accuracy-Results(Octave):
I added a complete example-project for reproduction:
libsvmtest.tar.gz
The FAQ only mentions
SVC_Q::get_Q
andSVR_Q::get_Q
to apply the OpenMP pragmas, so I did not apply it onONE_CLASS_Q::get_Q
for this experiment.OpenMP is therefore only used for the prediction.
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