scikit-learn__scikit-learn-14894

Based on the research, I can now generate the patch. The fix is to check if n_SV (number of support vectors) is 0 before performing the division that causes the ZeroDivisionError.

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Content

Based on the research, I can now generate the patch. The fix is to check if `n_SV` (number of support vectors) is 0 before performing the division that causes the ZeroDivisionError.

--- a/sklearn/svm/base.py
+++ b/sklearn/svm/base.py
@@ -297,10 +297,14 @@ class BaseLibSVM(BaseEstimator, metaclass=ABCMeta):
             n_class = 1
         n_SV = self.support_vectors_.shape[0]
 
         dual_coef_indices = np.tile(np.arange(n_SV), n_class)
-        dual_coef_indptr = np.arange(0, dual_coef_indices.size + 1,
-                                     dual_coef_indices.size / n_class)
-        self

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