Hi Peter.
What you try to achieve is currently not possible afaik
There was a branch by Noel to implement this but I'm not sure about it's
state.
You could give it a shot.
Alternatively you can use the IterGrid (or ParameterGrid in the dev
version I think)
from the grid_search module and write the for-loop yourself.
That shouldn't be too hard.
Hth,
Andy
On 05/31/2013 04:25 PM, Peter Retzlaff wrote:
> Hello everyone,
>
> I'm trying to execute a grid search with the GridSearchCV class (for an
> AdaBoostClassifier) and want to use a custom sample_weight vector to
> begin with. However, I can't figure out, how to do this. Passing the
> parameter to GridSearchCV's fit()-method gives me the message, that this
> is deprecated and will be ignored. Passing it to the
> GridSearch-constructor like so:
>
> grid = GridSearchCV(clf, params, fit_params={'sample_weights': my_weights})
>
> doesn't work either, because it tries to apply the same weights vector
> to each of the different folds, which of course doesn't make sense and
> fails because the size of my_weights doesn't correspond to the sizes of
> the folds. Can I somehow specify a weights vector for each fold? Is
> there an easier way? Is this even possible?
> I'm sorry, if I'm missing something obvious here.... By the way, I'm
> using the latest development version (0.14-git).
>
> Best regards.
> Peter
>
>
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