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scikit-learn__scikit-learn-25638

Based on the GitHub issue and my knowledge of the scikit-learn codebase, I can provide the patch. The issue is that nullable pandas dtypes ("Int64", "Float64", "boolean") are not properly handled when converted to numpy arrays - they…

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Content

Based on the GitHub issue and my knowledge of the scikit-learn codebase, I can provide the patch. The issue is that nullable pandas dtypes ("Int64", "Float64", "boolean") are not properly handled when converted to numpy arrays - they become `object` dtype instead of proper numeric types. 

The fix needs to be in `sklearn/utils/multiclass.py` where the `type_of_target` function needs to handle the conversion of pandas nullable dtypes before checking the type.

--- a/sklearn/utils/multiclass.py
+++ b/sklearn/utils/multiclass.py
@@ -155,6 +155,19 @@ def unique_labels(*ys):
     if not ys:
       

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