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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/02/10 09:10:19 UTC

[GitHub] [spark] zhengruifeng commented on a change in pull request #27519: [SPARK-30770][ML] avoid vector conversion in GMM.transform

zhengruifeng commented on a change in pull request #27519: [SPARK-30770][ML] avoid vector conversion in GMM.transform
URL: https://github.com/apache/spark/pull/27519#discussion_r376937067
 
 

 ##########
 File path: mllib-local/src/main/scala/org/apache/spark/ml/stat/distribution/MultivariateGaussian.scala
 ##########
 @@ -43,46 +43,40 @@ class MultivariateGaussian @Since("2.0.0") (
   require(cov.numCols == cov.numRows, "Covariance matrix must be square")
   require(mean.size == cov.numCols, "Mean vector length must match covariance matrix size")
 
-  /** Private constructor taking Breeze types */
-  private[ml] def this(mean: BDV[Double], cov: BDM[Double]) = {
-    this(Vectors.fromBreeze(mean), Matrices.fromBreeze(cov))
-  }
-
-  @transient private lazy val breezeMu = mean.asBreeze.toDenseVector
-
   /**
    * Compute distribution dependent constants:
    *    rootSigmaInv = D^(-1/2)^ * U.t, where sigma = U * D * U.t
    *    u = log((2*pi)^(-k/2)^ * det(sigma)^(-1/2)^)
    */
-  @transient private lazy val (rootSigmaInv: BDM[Double], u: Double) = calculateCovarianceConstants
+  @transient private lazy val tuple3 = {
 
 Review comment:
   it is said in [LeastSquaresAggregator](https://github.com/apache/spark/blob/12e1bbaddbb2ef304b5880a62df6683fcc94ea54/mllib/src/main/scala/org/apache/spark/ml/optim/aggregator/LeastSquaresAggregator.scala#L188) that 
   
   > // do not use tuple assignment above because it will circumvent the @transient tag

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