scikit-learn__scikit-learn-15512
Based on my knowledge of the scikit-learn codebase and the issue described, I can provide the patch. The issue is in the affinity_propagation_.py file where when the algorithm doesn't converge, it should return empty cluster centers and -1…
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Based on my knowledge of the scikit-learn codebase and the issue described, I can provide the patch. The issue is in the `affinity_propagation_.py` file where when the algorithm doesn't converge, it should return empty cluster centers and -1 labels as documented, but instead returns the last iteration's results.
Looking at the standard scikit-learn 0.20.x implementation, the fix needs to:
1. Add a convergence check after the main iteration loop
2. When not converged, set `cluster_centers_indices` to empty array and `labels` to -1
Here's the patch:
```
--- a/sklearn/cluster/affinity_propagat
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