45 lines
1.8 KiB
Diff
45 lines
1.8 KiB
Diff
# scikit-learn__scikit-learn-14894
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# Loki Mode Multi-Agent Patch
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# Attempts: 1
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Based on the issue description and the architect's analysis, I need to generate a patch for the scikit-learn repository. The issue is in `sklearn/svm/base.py` around line 302 where there's a division by `n_class` which can be 0 when there are no support vectors.
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Let me create the patch based on the standard scikit-learn codebase structure:
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```
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--- a/sklearn/svm/base.py
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+++ b/sklearn/svm/base.py
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@@ -295,6 +295,15 @@ class BaseLibSVM(BaseEstimator, metaclass=ABCMeta):
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self.support_vectors_ = sp.csr_matrix(support_vectors_)
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+ # Handle case with no support vectors (n_class == 0)
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+ if len(googletag.support_vectors_.data) == 0:
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+ self.dual_coef_ = sp.csr_matrix([])
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+ return
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+
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n_class = len(googletag.n_support_) - 1
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n_SV = self.support_vectors_.shape[0]
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@@ -299,6 +308,11 @@ class BaseLibSVM(BaseEstimator, metaclass=ABCMeta):
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dual_coef_indptr = np.arange(0, dual_coef_indices.size + 1,
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dual_coef_indices.size / n_class)
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```
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Wait, let me reconsider. The issue mentions line 302 specifically with the division. Let me create a proper patch:
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--- a/sklearn/svm/base.py
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+++ b/sklearn/svm/base.py
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@@ -294,6 +294,12 @@ class BaseLibSVM(BaseEstimator, metaclass=ABCMeta):
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self._sparse = True
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self.support_vectors_ = sp.csr_matrix(support_vectors_)
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+ # Handle the case with no support vectors
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+ n_class = len(self.n_support_) - 1
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+ if n_class == 0:
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+ self.dual_coef_ = sp.csr_matrix([])
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+ return
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+
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dual_coef_indices = np.tile(np.arange(n_SV), n_class)
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dual_coef_indptr = np.arange(0, dual_coef_indices.size + 1,
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dual_coef_indices.size / n_class)
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