Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16646#discussion_r97016294
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/r/GaussianMixtureWrapper.scala ---
@@ -124,7 +129,8 @@ private[r] object GaussianMixtureWrapper extends
MLReadable[GaussianMixtureWrapp
val rMetadataStr = sc.textFile(rMetadataPath, 1).first()
val rMetadata = parse(rMetadataStr)
val dim = (rMetadata \ "dim").extract[Int]
- new GaussianMixtureWrapper(pipeline, dim, isLoaded = true)
+ val logLikelihood = (rMetadata \ "logLikelihood").extract[Double]
+ new GaussianMixtureWrapper(pipeline, dim, logLikelihood, isLoaded =
true)
--- End diff --
Yeah, it will break existing persisted model, but I think we don't
guarantee mode persistent compatibility between different versions for SparkR.
We are planing to make model persistence consistent between SparkR and MLlib,
then there is no specific handling for SparkR and will let MLlib to handle all
model persistent issue.
However if we want to make model persistent compatibility for SparkR
currently, I can add code to handle different versions here but will lead
maintenance more complicated. What's your opinions?
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