1 class svm libsvm

For optimal performance, use C-ordered numpy. This allows you to change the request for some parameters and not others. I cannot leave the target column empty in the learner settings, so I appended a column with a constant value of 1 and defined it as the target column. If you have a lot of noisy observations you should decrease it: decreasing C corresponds to more regularization. Randomness of the underlying implementations : The underlying implementations of SVC and NuSVC use a random number generator only to shuffle the data for probability estimation when probability is set to True.

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