I guess my question was mostly about how gridsearch works with oneclass SVM
since once-class SVM does not take into account for labels
Thank you,
From: Pagliari, Roberto [mailto:[email protected]]
Sent: Friday, September 05, 2014 1:36 PM
To: [email protected]
Subject: [Scikit-learn-general] one-class SVM with limited number of samples
I am trying to train the one-class SVM.
According to libSVM
Q: How do I choose parameters for one-class SVM as training data are in only
one class?
You have pre-specified true positive rate in mind and then search for
parameters which achieve similar cross-validation accuracy.
But the one-class SVM does not take the labels as an input, as it only works on
X_train.
1. So how should cross-validation be performed, assuming the number of
samples with label '1' is extremely limited.
2. And what if there is none?
Thanks,
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