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doc/modules/cross_validation.rst
@@ -187,7 +187,7 @@ These prediction can then be used to evalute the classifier::
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>>> predicted = cross_validation.cross_val_predict(clf, iris.data,
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... iris.target, cv=10)
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>>> metrics.accuracy_score(iris.target, predicted) # doctest: +ELLIPSIS
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- 0.97...
+ 0.966...
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Note that the result of this computation may be slightly different from those
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obtained using :func:`cross_val_score` as the elements are grouped in different
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