From a9f3daaba688b41b6ae102f80e8d9d6cd1045322 Mon Sep 17 00:00:00 2001 From: Feynman Liang Date: Tue, 25 Aug 2015 11:58:47 -0700 Subject: [PATCH] [SPARK-10230] [MLLIB] Rename optimizeAlpha to optimizeDocConcentration See [discussion](https://github.com/apache/spark/pull/8254#discussion_r37837770) CC jkbradley Author: Feynman Liang Closes #8422 from feynmanliang/SPARK-10230. --- .../spark/mllib/clustering/LDAOptimizer.scala | 16 ++++++++-------- .../apache/spark/mllib/clustering/LDASuite.scala | 2 +- 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala index 5c2aae6403..38486e949b 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala @@ -258,7 +258,7 @@ final class OnlineLDAOptimizer extends LDAOptimizer { private var tau0: Double = 1024 private var kappa: Double = 0.51 private var miniBatchFraction: Double = 0.05 - private var optimizeAlpha: Boolean = false + private var optimizeDocConcentration: Boolean = false // internal data structure private var docs: RDD[(Long, Vector)] = null @@ -335,20 +335,20 @@ final class OnlineLDAOptimizer extends LDAOptimizer { } /** - * Optimize alpha, indicates whether alpha (Dirichlet parameter for document-topic distribution) - * will be optimized during training. + * Optimize docConcentration, indicates whether docConcentration (Dirichlet parameter for + * document-topic distribution) will be optimized during training. */ @Since("1.5.0") - def getOptimzeAlpha: Boolean = this.optimizeAlpha + def getOptimizeDocConcentration: Boolean = this.optimizeDocConcentration /** - * Sets whether to optimize alpha parameter during training. + * Sets whether to optimize docConcentration parameter during training. * * Default: false */ @Since("1.5.0") - def setOptimzeAlpha(optimizeAlpha: Boolean): this.type = { - this.optimizeAlpha = optimizeAlpha + def setOptimizeDocConcentration(optimizeDocConcentration: Boolean): this.type = { + this.optimizeDocConcentration = optimizeDocConcentration this } @@ -458,7 +458,7 @@ final class OnlineLDAOptimizer extends LDAOptimizer { // Note that this is an optimization to avoid batch.count updateLambda(batchResult, (miniBatchFraction * corpusSize).ceil.toInt) - if (optimizeAlpha) updateAlpha(gammat) + if (optimizeDocConcentration) updateAlpha(gammat) this } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala index 8a714f9b79..746a76a7e5 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/LDASuite.scala @@ -423,7 +423,7 @@ class LDASuite extends SparkFunSuite with MLlibTestSparkContext { val k = 2 val docs = sc.parallelize(toyData) val op = new OnlineLDAOptimizer().setMiniBatchFraction(1).setTau0(1024).setKappa(0.51) - .setGammaShape(100).setOptimzeAlpha(true).setSampleWithReplacement(false) + .setGammaShape(100).setOptimizeDocConcentration(true).setSampleWithReplacement(false) val lda = new LDA().setK(k) .setDocConcentration(1D / k) .setTopicConcentration(0.01)