I thought logistic regression used the log of the odds ratio to convert
what's essentially a linear regression into probability values. Can't we do
the same with the decision function of linear SVC?
But yes, it makes more sense to use logistic regression. I'll try that.
Thanks!
On Thu, Oct 23, 2
2014-10-23 16:21 GMT+02:00 George Bezerra :
> Is there a simple way to get the probabilities that a data point belongs to
> a class for this model?
SVMs aren't probability models. You can use LogisticRegression, that's
the same algorithm but with a different loss function.
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Hi George,
there is Platt scaling, which will turn your decision function into
something in the interval [0, 1]. However, these aren't really
probabilities (don't correspond to any probabilistic model).
sklearn.svm.SVC(kernel="linear", probability=True) provides a
`predict_proba` for you via this
I'm using the LinearSVC module but I noticed that it doesn't implement a
predict_proba method, only the decision_function method.
Is there a simple way to get the probabilities that a data point belongs to
a class for this model?
Thanks.
--
George Bezerra
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