Hi,
Could you provide some minimal data as to reproduce this behavior?
Best regards,
Arnaud
On 10 Jun 2014, at 16:53, Miguel Fernando Cabrera <[email protected]> wrote:
> Hi Everyone,
>
> This is my first post in the list. I have been using scikit-learn actively
> for the last six month in my M.Sc. thesis and now at my new job I want to
> use it for some tasks. I hope I can eventually become collaborator to the
> project.
>
> But lets start with a question :) - I wasn't sure if I should use
> StackOverflow for this. Please let me know if it so.
>
> I am using Scikit-learn for doing some multilabel classificaiton. I was
> trying to use both 0.14 and master. However, when using master I get an
> error. Even when using MultilabelBinarizer.
>
> So here's the code working in 0.14.
>
> #I instantiate the label binarizer to get the possible labels
> lb = LabelBinarizer().fit()
>
> # then I transfor the existing values (list of possible labels)
> y_train = lb.transform(y_val)
>
>
> svm = LinearSVC()
>
> ovr_svm = OneVsRestClassifier(svm)
>
> C_range = 2.0 ** np.arange(-2, 7)
>
> param_grid = dict(estimator__C=C_range)
>
> grid = GridSearchCV(estimator=ovr_svm,
> param_grid=param_grid,
> n_jobs=1,
> scoring='f1',
> cv=StratifiedKFold(y=y_train, n_folds=3),
> verbose=2)
>
> grid.fit(X_train, y_train)
>
> # This works OK, however when switching to 0.15 and using MultilabelBinarizer
> I get the following error:
>
>
>
> /Users/miguel/anaconda/envs/hclassifier/lib/python2.7/site-packages/sklearn/cross_validation.pyc
> in __init__(self, y, n_folds, indices, shuffle, random_state)
> 427 for test_fold_idx, per_label_splits in
> enumerate(zip(*per_label_cvs)):
> 428 for label, (_, test_split) in zip(unique_labels,
> per_label_splits):
> --> 429 label_test_folds = test_folds[y == label]
> 430 # the test split can be too big because we used
> 431 # KFold(max(c, self.n_folds), self.n_folds) instead of
>
> ValueError: boolean index array should have 1 dimension
>
>
> I have not been following the development of the 0.15 but based on the last
> e-mails there was some changes on the Multilabel representation. Maybe is
> related? What should I change to make my code work for 0.15?
>
>
> Thanks in advance,
>
>
> Cheers
> --
> Miguel Cabrera
> http://mfcabrera.com
> "A los hombres fuertes les pasa lo que a los barriletes; se elevan cuando es
> mayor el viento que se opone a su ascenso." - José Ingenieros
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