Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/18281#discussion_r128630645
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala ---
@@ -101,6 +101,45 @@ class OneVsRestSuite extends SparkFunSuite with
MLlibTestSparkContext with Defau
assert(expectedMetrics.confusionMatrix ~== ovaMetrics.confusionMatrix
absTol 400)
}
+ test("one-vs-rest: tuning parallelism does not change output") {
--- End diff --
So I know this would be annoying to do - but would it make sense to test
that we're actually training the models in parallel? I think we're probably
doing it correctly right now, but I could see this accidentally getting screwed
up and using the wrong execution context in the future.
---
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]
