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doc/glossary.rst
@@ -231,7 +231,7 @@ General Concepts
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cross validation
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A resampling method that iteratively partitions data into mutually
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exclusive 'train' and 'test' subsets so model performance can be
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- evaluated on unseen data. This conserves data as avoids the need to hold
+ evaluated on unseen data. This conserves data as it avoids the need to hold
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out a 'validation' dataset and accounts for variability as multiple
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rounds of cross validation are generally performed.
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See :ref:`User Guide <cross_validation>` for more details.
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