scikit-learn__scikit-learn-13241
Based on the issue description and my knowledge of scikit-learn's codebase, I can construct the appropriate patch. The fix involves:
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Content
Based on the issue description and my knowledge of scikit-learn's codebase, I can construct the appropriate patch. The fix involves:
1. Adding `svd_flip` import in `kernel_pca.py`
2. Applying `svd_flip` to the eigenvectors (`alphas_`) after the eigendecomposition to ensure consistent signs
In scikit-learn 0.18.x, the file is at `sklearn/decomposition/kernel_pca.py`. The key function is `_fit_transform` where eigenvectors are computed using either `linalg.eigh` or `eigsh` (arpack).
--- a/sklearn/decomposition/kernel_pca.py
+++ b/sklearn/decomposition/kernel_pca.py
@@ -12,6 +12,7 @@ from scip
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