As much as possible, parameters to a model should be specified to the class
constructor, not methods, even if application is there. This has been the
scikit-learn design for a while in order to enable things like grid search
and a bare-bones pipeline implementation. So external projects adding
additional args to predict may not have been correctly designed (and it's
easy enough for you to inherit from their model to fix the problem by
moving that param to the constructor). It may be valid to add a param to
predict when: (a) it is data-dependent, e.g. a parallel array to the
feature array; or (b) it modifies the output format of predict, e.g. to
return error as in GaussianProcess. Any uses of this are fundamentally
custom approaches for which Pipeline already has reduced utility, but I can
see how forwarding kwargs may give a minor convenience.
On 26 June 2015 at 03:35, Michael Kneier <michael.kne...@gmail.com> wrote:
> As far as I know, there aren't any estimators with predict kwargs. This
> doesn't mean that engineers aren't writing their own estimators, which may
> need kwargs. To me, one of sklearns great strengths is its pipeline, and
> extending its functionality to allow for more flexible estimator methods
> seems like a good thing. Perusing the sklearn github, it seems that there
> are is demand for extending the parameters pipeline accepts.
>
> If the yourself and the community prefer not to, that's fine. I think it
> is worth discussion though.
>
>
>
> On Wed, Jun 24, 2015 at 2:47 PM, Joel Nothman <joel.noth...@gmail.com>
> wrote:
>
>> What estimators have predict with multiple args? Without support for same
>> in cross validation routines and scorers, isn't t easier to write this
>> functionality in custom code as you need it, leaving the predictor off the
>> Pipeline?
>>
>> On 25 June 2015 at 06:06, Michael Kneier <michael.kne...@gmail.com>
>> wrote:
>>
>>> Hi all,
>>>
>>> It doesn't look like pipelines currently support passing kwargs to their
>>> estimators' predict method. I think it would be great to add this
>>> functionality, but I want to get your thoughts before I open a PR.
>>>
>>> Thanks,
>>> Mike
>>>
>>>
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>>
>>
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>
>
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