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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