atronchi commented on a change in pull request #26197: [SPARK-29577] Implement
p-value simulation and unit tests for chi2 test
URL: https://github.com/apache/spark/pull/26197#discussion_r338300773
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File path:
mllib/src/main/scala/org/apache/spark/mllib/stat/test/ChiSqTest.scala
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@@ -151,6 +155,8 @@ private[spark] object ChiSqTest extends Logging {
*/
def chiSquared(observed: Vector,
expected: Vector = Vectors.dense(Array.empty[Double]),
+ simulatePValue: Boolean = false,
Review comment:
I see. This looks like a good opportunity to bring ML into alignment with
MLlib since the ML implementation of Chi squared tests so far seems to only
include the independence test.
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/stat/ChiSquareTest.scala
It will probably take me a week or so, but I could work on migrating the
goodness of fit test and this p-value simulation into ML if that's the way to
go. Thoughts?
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