Hi,

If you want to get `sample_weights` working with the current master,
the easiest is to take PR 3524 and either pass it through `fit_params`
or just undo the last commit in the branch.

I needed to change a couple of things to get 1574 up to date with the
current master, but nothing else is changed.

Best,
Vlad

On Sun, Aug 3, 2014 at 6:47 AM, Joel Nothman <[email protected]> wrote:
> You could use the implementation of sample_weight support in
> cross-validation from
> https://github.com/scikit-learn/scikit-learn/pull/1574, which should work
> but doesn't have much in the way of tests. It may be superseded by
> https://github.com/scikit-learn/scikit-learn/pull/3524
>
>
> On 3 August 2014 14:05, Michael Anuzis <[email protected]> wrote:
>>
>> Greetings scikit-learn-general,
>>
>> Long time fan of scikit-learn, but my first post on this list. Appreciate
>> any insight or guidance you can share.
>>
>> I'm trying to implement my own scoring function for cross_val_score using
>> the make_scorer factory function. The evaluation I'm trying to build is for
>> a normalized weighted gini, which requires a "weights" array passed in to
>> calculate the relative weight of each row.
>>
>> The function works fine when called manually with (y_true, y_pred), but
>> raises an AssertionError when called as a parameter on
>> cross_val_score(scoring=gini_function)... I think the error might be due to
>> the weights array being its original size, while the (y_true, y_pred) arrays
>> might be reduced sizes for cross-validation folds.
>>
>> Here's my code and the stack trace:
>>
>> https://dpaste.de/Zk6n
>>
>> Appreciate any suggestions,
>> -Michael
>>
>>
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