Hi Ryan.
I don't think there's a good solution. Feel free to open an issue in the
issue tracker (I'm not aware of one for this).
You can access the pipeline steps, so you can access the kneighbors
method via the "steps" attribute, but that wouldn't
take any of the previous steps into account, and so you lose all the
benefits of the pipeline.
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.
Andy
On 09/12/2017 04:01 PM, Ryan Conway wrote:
Hello,
I'm wondering if sklearn provides a means of terminating pipelines
with a NearestNeighbors search.
For example, my workflow is DictVectorizer -> TfidfTransformer ->
NearestNeighbors. I'd like to capture this in an sklearn Pipeline.
Unfortunately, Pipeline does not expose a kneighbors() method that
would run all intermediate transforms and then return the result of
NearestNeighbors.kneighbors().
I went through Pipeline's source and noticed its decision_function(),
predict() etc. all capture this functionality with different
terminating operation names. Maybe there is some way to specify the
terminating operation method name rather than relying on these
Pipeline methods?
Thank you,
Ryan
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