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@@ -148,7 +148,7 @@ against features with very large variances exerting an overly large influence du
following parameters in the constructor:
* `withMean` False by default. Centers the data with mean before scaling. It will build a dense
-output, so this does not work on sparse input and will raise an exception.
+output, so take care when applying to sparse input.
* `withStd` True by default. Scales the data to unit standard deviation.
We provide a [`fit`](api/scala/index.html#org.apache.spark.mllib.feature.StandardScaler) method in