Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16464#discussion_r95954100
--- 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 --
In MLlib, if the model is ```DistributedLDAModel```, it has variables
called ```trainingLogLikelihood``` and ```logPrior```. If the model is
```LocalLDAModel```, there is no above variables exist, we can not tell users
whether they are numeric. So I'd prefer ```NULL``` to represent not existing.
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