Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/7916#discussion_r36156091
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala ---
@@ -267,32 +272,35 @@ class LocalLDAModel private[clustering] (
// by topic (columns of lambda)
val Elogbeta = LDAUtils.dirichletExpectation(lambda.t).t
- var score = documents.filter(_._2.numNonzeros > 0).map { case (id:
Long, termCounts: Vector) =>
- var docScore = 0.0D
- val (gammad: BDV[Double], _) =
OnlineLDAOptimizer.variationalTopicInference(
- termCounts, exp(Elogbeta), brzAlpha, gammaShape, k)
- val Elogthetad: BDV[Double] = LDAUtils.dirichletExpectation(gammad)
-
- // E[log p(doc | theta, beta)]
- termCounts.foreachActive { case (idx, count) =>
- docScore += count * LDAUtils.logSumExp(Elogthetad + Elogbeta(idx,
::).t)
- }
- // E[log p(theta | alpha) - log q(theta | gamma)]; assumes alpha is
a vector
- docScore += sum((brzAlpha - gammad) :* Elogthetad)
- docScore += sum(lgamma(gammad) - lgamma(brzAlpha))
- docScore += lgamma(sum(brzAlpha)) - lgamma(sum(gammad))
-
- docScore
- }.sum()
+ // Sum bound components for each document:
+ // component for prob(tokens) + component for prob(document-topic
distribution)
--- End diff --
Yes, it was meant to be clearer...hm
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