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"How to interpret One-class SVM output?"
mohammadreza
Member Posts: 23 
Contributor II
Hi gurus,
I have used one-class SVM for binary classification in RapidMiner. I only trained the model with false examples. And the output is "inside" either "outside". Now in order to calculate precision and recall, I need true positive, false positive and so on. But due to the fact that I trained the model only with false examples, I am not sure if the following is right:
"inside = non-anomaly=false"
"outside = anomaly=true"
Thanks in advance for any idea which may help me come out of this confusion.
I have used one-class SVM for binary classification in RapidMiner. I only trained the model with false examples. And the output is "inside" either "outside". Now in order to calculate precision and recall, I need true positive, false positive and so on. But due to the fact that I trained the model only with false examples, I am not sure if the following is right:
"inside = non-anomaly=false"
"outside = anomaly=true"
Thanks in advance for any idea which may help me come out of this confusion.
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Answers
It was not a good idea for my problem to train the classifier with negative samples. I trained it with anomalies and the precision and recall have their original meaning now.