Github user yu-iskw commented on a diff in the pull request:
https://github.com/apache/spark/pull/6791#discussion_r32882080
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala ---
@@ -465,6 +465,36 @@ private[python] class PythonMLLibAPI extends
Serializable {
}
/**
+ * Java stub for Python mllib LDA.run()
+ */
+ def trainLDAModel(
+ data: JavaRDD[LabeledPoint],
--- End diff --
Umm, it is a little difficult to decide which is the better. The different
point between yours and mine from the users point of view are :
- Each row type is an array or a tuple
- Feature data type is array or DenceVector/SparceVector
- Does yours support sparce vector?
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