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Documentation update: Small text fix #42

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Expand Up @@ -39,7 +39,7 @@ These metrics are translated into three measures provided by Azure AI Language:

With a single label project, you can identify which classes aren't classified as well as others and find more quality data to use in training your model. For multiple label projects, figuring out quality data becomes more complex due to the matrix of possible permutations of combined labels.

For example, let's your model is correctly classifying "Action" games and some "Action and Strategy" games, but failing at "Strategy" games. To improve your model, you'll want to find more high quality and varied summaries for both "Action and Strategy" games, as well as "Strategy" games to teach your model how to differentiate the two. This challenge increases exponentially with more possible classes your model is classifying into.
For example, let's say your model is correctly classifying "Action" games and some "Action and Strategy" games, but failing at "Strategy" games. To improve your model, you'll want to find more high quality and varied summaries for both "Action and Strategy" games, as well as "Strategy" games to teach your model how to differentiate the two. This challenge increases exponentially with more possible classes your model is classifying into.

### API payload

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