Joel is right.
In fact, you usually don't want to tune a lot the sample weights: you may leave
them default, set them in order to balance classes, or fix them according to
some business rule.
That said, you can always run a couple of grid searchs changing that sample
weights and compare results afterwards.
--
Julio
> El 24 jun 2017, a las 15:51, Joel Nothman <joel.noth...@gmail.com> escribió:
>
> yes, trying multiple sample weightings is not supported by grid search
> directly.
>
>> On 23 Jun 2017 6:36 pm, "Manuel Castejón Limas" <manuel.caste...@gmail.com>
>> wrote:
>> Dear Joel,
>>
>> I tried and removed the square brackets and now it works as expected for a
>> single sample_weight vector:
>>
>> validator = GridSearchCV(my_Regressor,
>> param_grid={'number_of_hidden_neurons': range(4, 5),
>> 'epochs': [50],
>> },
>> fit_params={'sample_weight': my_sample_weights },
>> n_jobs=1,
>> )
>> validator.fit(x, y)
>> The problem now is that I want to try multiple trainings with multiple
>> sample_weight parameters, in the following fashion:
>>
>> validator = GridSearchCV(my_Regressor,
>> param_grid={'number_of_hidden_neurons': range(4, 5),
>> 'epochs': [50],
>> 'sample_weight': [my_sample_weights,
>> my_sample_weights**2] ,
>> },
>> fit_params={},
>> n_jobs=1,
>> )
>> validator.fit(x, y)
>> But unfortunately it produces the same error again:
>>
>> ValueError: Found a sample_weight array with shape (1000,) for an input with
>> shape (666, 1). sample_weight cannot be broadcast.
>>
>> I guess that the issue is that the sample__weight parameter was not thought
>> to be changed during the tuning, was it?
>>
>>
>> Thank you all for your patience and support.
>> Best
>> Manolo
>>
>>
>>
>>
>> 2017-06-23 1:17 GMT+02:00 Manuel CASTEJÓN LIMAS <mc...@unileon.es>:
>>> Dear Joel,
>>> I'm just passing an iterable as I would do with any other sequence of
>>> parameters to tune. In this case the list only has one element to use but
>>> in general I ought to be able to pass a collection of vectors.
>>> Anyway, I guess that that issue is not the cause of the problem.
>>>
>>> El 23 jun. 2017 1:04 a. m., "Joel Nothman" <joel.noth...@gmail.com>
>>> escribió:
>>>> why are you passing [my_sample_weights] rather than just my_sample_weights?
>>>>
>>
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