Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4419#discussion_r29296360
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -98,13 +94,38 @@ class EMLDAOptimizer extends LDAOptimizer{
/**
* Compute bipartite term/doc graph.
*/
- private[clustering] override def initialState(
- docs: RDD[(Long, Vector)],
- k: Int,
- docConcentration: Double,
- topicConcentration: Double,
- randomSeed: Long,
- checkpointInterval: Int): LDAOptimizer = {
+ private[clustering] override def initialize(docs: RDD[(Long, Vector)],
lda: LDA):
+ LDAOptimizer = {
+
+ val docConcentration = lda.getDocConcentration
+ val topicConcentration = lda.getTopicConcentration
+ val k = lda.getK
+
+ /**
+ * Note: The restriction > 1.0 may be relaxed in the future (allowing
sparse solutions),
+ * but values in (0,1) are not yet supported.
+ */
+ require(docConcentration > 1.0 || docConcentration == -1.0, s"LDA
docConcentration must be" +
+ s" > 1.0 (or -1 for auto) for EM Optimizer, but was set to
$docConcentration")
+ require(topicConcentration > 1.0 || topicConcentration == -1.0, s"LDA
topicConcentration " +
+ s"must be > 1.0 (or -1 for auto) for EM Optimizer, but was set to
$topicConcentration")
+
+ /**
+ * - For EM: default = (50 / k) + 1.
--- End diff --
No need to duplicate this comment since it's already in the Scala doc above
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