Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4419#discussion_r29296377
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala ---
@@ -208,3 +225,224 @@ class EMLDAOptimizer extends LDAOptimizer{
new DistributedLDAModel(this, iterationTimes)
}
}
+
+
+/**
+ * :: Experimental ::
+ *
+ * An online optimizer for LDA. The Optimizer implements the Online LDA
algorithm, which
+ * processes a subset of the corpus by each call to next, and update the
term-topic
+ * distribution adaptively.
+ *
+ * References:
+ * Hoffman, Blei and Bach, "Online Learning for Latent Dirichlet
Allocation." NIPS, 2010.
+ */
+@Experimental
+class OnlineLDAOptimizer extends LDAOptimizer {
+
+ // LDA common parameters
+ private var k: Int = 0
+ private var D: Int = 0
+ private var vocabSize: Int = 0
+ private var alpha: Double = 0
+ private var eta: Double = 0
+ private var randomSeed: Long = 0
+
+ // Online LDA specific parameters
+ private var tau_0: Double = -1
+ private var kappa: Double = -1
+ private var batchSize: Int = -1
+
+ // internal data structure
+ private var docs: RDD[(Long, Vector)] = null
+ private var lambda: BDM[Double] = null
+ private var Elogbeta: BDM[Double]= null
+ private var expElogbeta: BDM[Double] = null
+
+ // count of invocation to next, used to help deciding the weight for
each iteration
+ private var iteration = 0
+
+ /**
+ * A (positive) learning parameter that downweights early iterations
+ */
+ def getTau_0: Double = {
+ if (this.tau_0 == -1) {
--- End diff --
This default is not problem-dependent, so I'd recommend initializing the
value to 1024 and not having a special value -1. Can you please also make this
fix for other parameters with defaults?
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