Github user VinceShieh commented on a diff in the pull request:
https://github.com/apache/spark/pull/14858#discussion_r76571166
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/Bucketizer.scala
---
@@ -63,7 +63,7 @@ final class Bucketizer @Since("1.4.0") (@Since("1.4.0")
override val uid: String
/** @group setParam */
@Since("1.4.0")
- def setSplits(value: Array[Double]): this.type = set(splits, value)
+ def setSplits(value: Array[Double]): this.type = set(splits,
value.filter(!_.isNaN))
--- End diff --
rejecting? do you mean we throw an error for splits with NaN ?
User might not specify NaN bounded splits, but it could be set by other
function calls, such as approxQuantile, from a dataset with quite a number of
NaN
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