Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/14858#discussion_r77489786
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/QuantileDiscretizer.scala ---
@@ -114,10 +115,10 @@ final class QuantileDiscretizer @Since("1.6.0")
(@Since("1.6.0") override val ui
splits(0) = Double.NegativeInfinity
splits(splits.length - 1) = Double.PositiveInfinity
- val distinctSplits = splits.distinct
+ val distinctSplits = splits.filter(!_.isNaN).distinct
--- End diff --
What would you do with NaN in approxQuantile except ignore it? it can't
affect a quantile. The question of what the bucketizer should do with NaN is
separate. I'd still favor one behavior there, but keeping that separate, let's
figure out what approxQuantile should do.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
