Github user GayathriMurali commented on a diff in the pull request:
https://github.com/apache/spark/pull/13176#discussion_r64075252
--- Diff: docs/ml-features.md ---
@@ -1064,7 +1069,8 @@ categorical features.
The bin ranges are chosen by taking a sample of the data and dividing it
into roughly equal parts.
The lower and upper bin bounds will be `-Infinity` and `+Infinity`,
covering all real values.
This attempts to find `numBuckets` partitions based on a sample of the
given input data, but it may
-find fewer depending on the data sample values.
+find fewer depending on the data sample values. Relative precision of the
approxQuantile is set using
--- End diff --
@MLnick @oliverpierson I can fix the `approxQuantile` documentation on
Scala side and python side to be more consistent with QuantileDiscretizer in
DataFrameStat in this JIRA itself. Please let me know if that makes sense
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