Pipelines are useful for creating composite estimators that can be plugged in elsewhere. At the moment we have nowhere you can plug in a neighborhood calculator, although we would like to (see https://github.com/scikit-learn/scikit-learn/pull/8999 for the latest attempt). If there are then compelling use-cases for allowing that pluggable neighbors estimator to be a pipeline, we might follow that path. But as you implied, we don't want to confuse users if such use-cases are far fetched.
What do you intend to use it for? On 15 September 2017 at 02:47, Ryan Conway <ryanmackenziecon...@gmail.com> wrote: > Thank you, Andreas. Indeed this becomes cumbersome when we don't know the > prototype of the terminating function. > > > it's pretty easy to implement this by creating your own Pipeline > subclass, isn't it? > > Good idea, that's probably the route I will take. That said, as a > newcomer to sklearn, a benefit of utility classes such as Pipeline is that > their interface helps me understand the library developers' intent and how > its components should fit together. Prior to this conversation I lacked > confidence that Pipeline was suitable for my use case. > > Ryan > > On Wed, Sep 13, 2017 at 2:14 PM, Joel Nothman <joel.noth...@gmail.com> > wrote: > >> it's pretty easy to implement this by creating your own Pipeline >> subclass, isn't it? >> >> On 14 Sep 2017 4:55 am, "Gael Varoquaux" <gael.varoqu...@normalesup.org> >> wrote: >> >>> On Wed, Sep 13, 2017 at 02:45:41PM -0400, Andreas Mueller wrote: >>> > We could add a way to call non-standard methods, but I'm not sure that >>> is the >>> > right way to go. >>> > (like pipeline.custom_method(X, method="kneighbors")). But that >>> assumes that >>> > the method signature is X or (X, y). >>> > So I'm not sure if this is generally useful. >>> >>> I don't see either why it's useful. We shouldn't add a method for >>> everything that can be easily coded with a few lines of Python. The nice >>> thing of Python is that it is such an expressive language. >>> >>> Gaël >>> _______________________________________________ >>> scikit-learn mailing list >>> scikit-learn@python.org >>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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