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Fix formatting
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jarrodmillman committed Jan 10, 2025
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4 changes: 2 additions & 2 deletions packages/scikit-learn/index.rst
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Expand Up @@ -999,13 +999,13 @@ overall performance of an algorithm. It appears in the bottom row
of the classification report; it can also be accessed directly::

>>> metrics.f1_score(y_test, y_pred, average="macro")
np.float64(0.991367...)
0.991367...

The over-fitting we saw previously can be quantified by computing the
f1-score on the training data itself::

>>> metrics.f1_score(y_train, clf.predict(X_train), average="macro")
np.float64(1.0)
1.0

.. note::

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