Github user oliverpierson commented on a diff in the pull request:
https://github.com/apache/spark/pull/11319#discussion_r53934003
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/QuantileDiscretizer.scala ---
@@ -103,6 +103,13 @@ final class QuantileDiscretizer(override val uid:
String)
@Since("1.6.0")
object QuantileDiscretizer extends
DefaultParamsReadable[QuantileDiscretizer] with Logging {
+
+ /**
+ * Minimum number of samples required for finding splits, regardless of
number of bins. If
+ * the dataset has less rows than this value, the entire dataset column
will be used.
+ */
+ val minSamplesRequired: Int = 10000
--- End diff --
I don't think you're missing anything. It's my first time contributing and
I just want to be explicit for reviewers of the patch. I agree that 10K isn't
that big, especially out "in the wild". However, I wasn't sure if there were
standards for time/memory consumption for tests so I added the line note so
that reviewers with more experience would be aware in case there are
established/de facto testing standards.
I'll make the "->" changes you've indicated and push a new commit sometime
today. Thanks.
---
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]
