ted):
118 # let unexpected exceptions pass through
AssertionError: ValueError not raised
On Tue, Jul 25, 2017 at 12:54 AM, Joel Nothman
wrote:
> what is the failing test? please provide the full traceback.
>
> On 24 Jul 2017 10:58 pm, "Sam Barnett" wrote:
>
>
7;Shape of input is different from what was
seen'
'in `fit`')
On Tue, Jul 25, 2017 at 9:41 AM, Sam Barnett wrote:
> This is the Traceback I get:
>
>
> AssertionErrorTraceback (most recent call last)
> in ()
> > 1 check_es
would be to compute the full kernel matrix in
> advance and pass that to GridSearchCV.
>
> You probably don't need it here, but you should also checkout what the
> _pairwise attribute does in cross-validation,
> because that it likely to come up when playing with kernels.
>
>
as Mueller wrote:
> Hi Sam.
> You need to put these into a reachable namespace (possibly as private
> functions) so that they can be pickled.
> Please stay on the sklearn mailing list, I might not have time to reply.
>
> Andy
>
>
> On 08/03/2017 01:24 PM, Sam Barnett wrote
To all,
I am working on a scikit-learn estimator that performs a version of SVC
with a custom kernel. Unfortunately, I have been presented with a problem:
when running a grid search (or even using the cross_val_score function), my
estimator encounters an overflow error when evaluating my kernel
(s
I am rolling classifier based on SVC which computes a custom Gram matrix
and runs this through the SVC classifier with kernel = 'precomputed'. While
this works fine with the fit method, I face a dilemma with the predict
method, shown here:
def predict(self, X):
"""Run the predict meth
quot;precomputed" kernels.
>
> Thanks
>
> Andy
>
>
> On 08/17/2017 05:22 AM, Sam Barnett wrote:
>
> I am rolling classifier based on SVC which computes a custom Gram matrix
> and runs this through the SVC classifier with kernel = 'precomputed'. While
>
