[scikit-learn] Issue regarding Feature Union
Chris Aridas
chris at aridas.eu
Thu May 6 06:45:30 EDT 2021
Hi,
Assuming that you have trained your pipeline, the following piece of
code should work.
pipeline.named_steps["feature_sel"].transform(X)
Best,
Chris
On Thu, May 6, 2021 at 12:52 PM mitali katoch <mitalikatoch at gmail.com>
wrote:
> Dear Scikit team,
>
> I am working with FeatureUnion in the pipeline and best parameters are as
> follows:
> Pipeline(steps=[('feature_sel',
> FeatureUnion(transformer_list= [ ('selectk',
> SelectKBest(k=500)),
> ('sel_fromModel',
>
> SelectFromModel(estimator=LogisticRegression(C=1,
>
> penalty='l1',
>
> solver='liblinear'),
>
> max_features=100))]
> )),
> ('sampler', SMOTE(k_neighbors=2, random_state=10)),
> ('model', SVC(random_state=10))]
> )
>
> I would like to extract those SelectKBest(k=500) and max_features=100 from
> the pipeline.
>
> Could you please confirm whether it is possible to do it, If yes, could
> you share the solution, I would highly appreciate that.
>
> Thanks in advance.
>
> Best Regards,
> Mitali Katoch
>
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