[scikit-learn] OneClassSvm | Different results on different runs

[Abhishek Raj]

Hi,

I am using one class svm for developing an anomaly detection model. I
observed that different runs of training on the same data set outputs
different accuracy. One run takes the accuracy as high as 98% and another
run on the same data brings it down to 93%. Googling a little bit I found
out that this is happening because of the random_state
<http://scikit-learn.org/stable/modules/generated/sklearn.utils.check_random_state.html>
parameter
but I am not clear of the details.

Can anyone expand on how is the parameter exactly affecting my training and
how I can figure out the best value to get the model with best accuracy?

Thanks,
Abhishek
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