> My preferred way of implementing that would be a generic,
> stateless transformer class that just runs a function on X in
> transform and returns the result.
I think this is useful anyway, and an effective but not ideal solution
for this use-case. Here that makes a lot of overhead for what is
re
Thanks for the great replies. As Lars rightly points out, I could define a
custom transform to accomplish the combining.
I do think that this could be more intuitively implemented (or at least
built in to FeatureUnion), and I'd like pitch in on the
https://github.com/scikit-learn/scikit-learn/issu
2014-02-27 23:37 GMT+01:00 Joel Nothman :
> I think it would be nice if the FeatureUnion makes it easy to extract
> only certain parts of the input for each transformer.
> https://github.com/scikit-learn/scikit-learn/issues/2034 intends to
> cover this issue, but we haven't resolved a clean API.
>
> The problem with FeatureUnion is that it can only combine the output of two
> transformers. I think it would be great to have a simple method of combining
> the result of a transformer with extrenal/untransformed data within a
> pipeline.
I think it would be nice if the FeatureUnion makes it
2014-02-27 8:33 GMT+01:00 michael kneier :
> I would like to add a "combiner" class which would work with pipeline to
> allow users to augment the output of scikit's text feature extraction process
> (or other feature extraction processes). For example, after apply
> CountVectorizer, it is somet
The problem with FeatureUnion is that it can only combine the output of two
transformers. I think it would be great to have a simple method of combining
the result of a transformer with extrenal/untransformed data within a pipeline.
Sent from my iPhone
On Feb 26, 2014, at 11:37 PM, Alexandre Gr
hi,
do you know:
http://scikit-learn.org/stable/modules/generated/sklearn.pipeline.FeatureUnion.html
?
it might do already what you want
A
On Thu, Feb 27, 2014 at 8:33 AM, michael kneier
wrote:
> Hi all,
>
> I would like to add a "combiner" class which would work with pipeline to
> allow u
Hi all,
I would like to add a "combiner" class which would work with pipeline to allow
users to augment the output of scikit's text feature extraction process (or
other feature extraction processes). For example, after apply CountVectorizer,
it is sometime desirable to augment the resulting dat
