[scikit-learn] Fwd: sample_weight parameter is not split when used in GridSearchCV

[Manuel CASTEJÓN LIMAS]

Hello Antonio,

Sure:

import sklearn
print(sklearn.__version__)
0.18.1


The error suggests that the fit function is expecting a split vector with
size 2/3*1000 but the whole vector (size 1000) is passed.

...
ValueError: Found a sample_weight array with shape (1000,) for an
input with shape (666, 1). sample_weight cannot be broadcast.



El 22 jun. 2017 11:49 p. m., "Julio Antonio Soto de Vicente" <julio at esbet.es>
escribió:

Hi Manuel,

Are you sure that you are using the latest version (or at least >0.17)? The
code for splitting the sample weights in GridSearchCV has been there for a
while now...

--
Julio

El 22 jun 2017, a las 23:33, Manuel Castejón Limas <
manuel.castejon at gmail.com> escribió:

Dear all,
I posted the full question on StackOverflow and as it contains some figures
I refer you to that post.

https://stackoverflow.com/questions/44661926/sample-weight-
parameter-shape-error-in-scikit-learn-gridsearchcv/44662285#44662285

I currently  believe that this issue is a bug and I opened an issue on
GitHub.

To sum up, the issue is that GridSearchCV does not handle the splitting of
the sample_weight vector during cross validation.

Nota bene: cross_val_score seems to handle the splitting OK, this issue
seems to occurr only in GridSearchCV.

Any comments enlightening me and showing me how wrong I am are most welcome.




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