DOC Fix typos in Visualizations docs
@@ -13,7 +13,7 @@ Visualizations
Scikit-learn defines a simple API for creating visualizations for machine
learning. The key feature of this API is to allow for quick plotting and
visual adjustments without recalculation. We provide `Display` classes that
-exposes two methods allowing to make the plotting: `from_estimator` and
+expose two methods for creating plots: `from_estimator` and
`from_predictions`. The `from_estimator` method will take a fitted estimator
and some data (`X` and `y`) and create a `Display` object. Sometimes, we would
like to only compute the predictions once and one should use `from_predictions`
@@ -42,7 +42,7 @@ ROC curve for SVC in future plots. In this case, the `svc_disp` is a
:class:`~sklearn.metrics.RocCurveDisplay` that stores the computed values as
attributes called `roc_auc`, `fpr`, and `tpr`. Be aware that we could get
the predictions from the support vector machine and then use `from_predictions`
-instead of `from_estimator` Next, we train a random forest classifier and plot
+instead of `from_estimator`. Next, we train a random forest classifier and plot
the previously computed roc curve again by using the `plot` method of the
`Display` object.
