As a generic answer, no. You'll have to write the equivalent of the
predict method yourself given the internal state (or, parameters) of the
trained classifier. For classifiers like SVM you can use libSVM directly
and avoid the Python wrapper.
On Mon, Sep 23, 2013 at 3:28 PM, Fred Baba <[email protected]> wrote:
> I'd like to use classifiers trained via sklearn in a real-time
> application, performance critical application. How do I access the internal
> representation of trained classifiers?
>
> For linear classifiers/regressions, I can simply store the coefficients
> and generate the linear combination myself. For tree regressions, I can use
> sklearn.tree.export_graphviz. Ideally there would be an export facility for
> all classifiers (particularly for examining the structure of generated
> models). Is there a general solution way to do this?
>
>
>
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