I'd recommend Joel's suggestion for the short term.
I wonder if that check could be removed -- as long as the input is
fancy-indexable, the code should otherwise not have an issue (until it hits
the distance metric, in which case you have that covered).
On 10 January 2014 13:09, Joel Nothman <joel.noth...@gmail.com> wrote:
> Can you just reshape your 3d array to a 2d array, and then reshape when
> input by your distance metric?
>
>
> On 10 January 2014 12:59, Mark Regan <m...@thinkvein.com> wrote:
>
>> Hi all,
>>
>> tldr: Is there a way for me to pass a 3D array to KNearestNeighbour?
>>
>> I have constructed a custom distance metric to be used with KNN. It takes
>> *two
>> 2D arrays* and returns a float. I believe this fits the requirements for
>> a distance metric in sklearn.
>>
>> However, I am unable to pass a 3D array to KNearestNeighbour. I get the
>> following error:
>>
>> /Library/Python/2.7/site-packages/sklearn/neighbors/base.pyc in _fit(self,
>> X) 178 179 if X.ndim != 2:--> 180 raise
>> ValueError("data type not understood") 181 182 n_samples =
>> X.shape[0]
>> ValueError: data type not understood
>>
>>
>> Is there a way for me to pass a non 2D array to KNearestNeighbour? For
>> context, I'm implementing a 1NN with Dynamic Time Warping.
>>
>> If not, is there a work around or a suggestion?
>>
>> Many thanks
>> Mark
>>
>>
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