Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/16009#discussion_r90330019
--- Diff: docs/ml-features.md ---
@@ -1188,7 +1188,9 @@ categorical features. The number of bins is set by
the `numBuckets` parameter. I
that the number of buckets used will be smaller than this value, for
example, if there are too few
distinct values of the input to create enough distinct quantiles.
-NaN values: Note also that QuantileDiscretizer
+NaN values:
+NaN values will be removed from the column during `QuantileDiscretizer`
fitting. This will produce
+a `Bucketizer` model for making predictions. During the transformation,
`Bucketizer`
--- End diff --
QuantileDiscretizer always drops NaNs during fitting, so it will not throw
an error for a dataset with NaNs even if handleInvalid = "error"
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