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Using scikit-learn's SGDClassifier to implement SVM: how to tune the regularization parameter?

原文 2019-12-25 19:27:02 5 1 python/ scikit-learn/ svm

I am using scikit-learn library to implement SVM for a large-size dataset (300-400K samples with <100 features). To cope with the size issue, I am using SGDClassifier rather than libsvm , however I am not aware of any argument/parameter so that I can tune the regularization parameter within SGDClassifier . Can anybody help me with this?

Thanks, Soheil

1 answers

You have to use the arguments - penalty and alpha. And l1_ratio if you consider elastic net.

Look at this

https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html

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Using scikit-learn's SGDClassifier to implement SVM: how to tune the regularization parameter?

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solution1 0 2019-12-25 19:33:42

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0 2019-12-25 19:33:42