From 9f450441fbb5b9a5037b05736a6a0468ad0925c0 Mon Sep 17 00:00:00 2001 From: Yanbo Liang Date: Tue, 25 Oct 2016 09:06:55 -0700 Subject: [PATCH] Fix build error for Scala 2.10. --- .../spark/ml/optim/WeightedLeastSquaresSuite.scala | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala index 5f638b488005..3cdab0327991 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala @@ -280,7 +280,7 @@ class WeightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext } // Cholesky also fails when regularization is added but we don't wish to standardize - val wls = new WeightedLeastSquares(true, regParam = 0.5, elasticNetParam = 0.0, + val wls = new WeightedLeastSquares(fitIntercept = true, regParam = 0.5, elasticNetParam = 0.0, standardizeFeatures = false, standardizeLabel = false, solverType = WeightedLeastSquares.Cholesky) intercept[SingularMatrixException] { @@ -470,10 +470,11 @@ class WeightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext var idx = 0 for (fitIntercept <- Seq(false, true); regParam <- Seq(0.1, 0.5, 1.0); - standardizeFeatures <- Seq(false, true); + standardization <- Seq(false, true); elasticNetParam <- Seq(0.1, 0.5, 1.0)) { - val wls = new WeightedLeastSquares(fitIntercept, regParam, elasticNetParam = elasticNetParam, - standardizeFeatures, standardizeLabel = true, solverType = WeightedLeastSquares.Auto) + val wls = new WeightedLeastSquares(fitIntercept, regParam, elasticNetParam, + standardizeFeatures = standardization, standardizeLabel = true, + solverType = WeightedLeastSquares.Auto) .fit(instances) val actual = Vectors.dense(wls.intercept, wls.coefficients(0), wls.coefficients(1)) assert(actual ~== expected(idx) absTol 1e-4) @@ -528,10 +529,10 @@ class WeightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext var idx = 0 for (fitIntercept <- Seq(false, true); regParam <- Seq(0.0, 0.1, 1.0); - standardizeFeatures <- Seq(false, true)) { + standardization <- Seq(false, true)) { for (solver <- WeightedLeastSquares.supportedSolvers) { val wls = new WeightedLeastSquares(fitIntercept, regParam, elasticNetParam = 0.0, - standardizeFeatures, standardizeLabel = true, solverType = solver) + standardizeFeatures = standardization, standardizeLabel = true, solverType = solver) .fit(instances) val actual = Vectors.dense(wls.intercept, wls.coefficients(0), wls.coefficients(1)) assert(actual ~== expected(idx) absTol 1e-4)