@Emily If you want to use SVM's to do this,
LinearSVC, NuSVC and SVC all three have the `class_weight` parameter
as far as I know, but just make sure as Olivier said.

2012/6/5 Olivier Grisel <[email protected]>

> 2012/6/5 Jaques Grobler <[email protected]>:
>
Hi,
>
> I'm new to scikit and machine learning in general and I trying to use svm
> to find the best way to classify a dataset containing lots of negatives. I
> was wondering if there is a way to increase the penalty factor associated
> with misclassification of the positive class?
> Thanks,
>
> Emily

> I'm not that clued up about this specifically, but I'd think that using
> > the `class_weight` parameter for the svm classifier in sklearn should
> > achieve this.
>
> Yes class_weight should be able to address that. Not all classifiers
> support it though, please check the docstrings.
>
> --
> Olivier
> http://twitter.com/ogrisel - http://github.com/ogrisel
>
>
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