Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16464#discussion_r95948100
--- Diff: R/pkg/R/mllib_clustering.R ---
@@ -404,11 +411,14 @@ setMethod("summary", signature(object = "LDAModel"),
vocabSize <- callJMethod(jobj, "vocabSize")
topics <- dataFrame(callJMethod(jobj, "topics",
maxTermsPerTopic))
vocabulary <- callJMethod(jobj, "vocabulary")
+ trainingLogLikelihood <- callJMethod(jobj,
"trainingLogLikelihood")
+ logPrior <- callJMethod(jobj, "logPrior")
--- End diff --
I think it's more appropriate to return ```NULL``` rather than ```NaN```
for local LDA model, since the ```logPrior``` is not existing rather than not a
number.
BTW, I think we can return NULL directly according to ```isDistributed```,
otherwise, call corresponding Scala methods. This should reduce the complexity
of ```LDAWrapper``` and reduce communication between R and Scala.
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