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authorYanbo Liang <ybliang8@gmail.com>2016-10-25 10:22:02 -0700
committerYanbo Liang <ybliang8@gmail.com>2016-10-25 10:22:02 -0700
commitac8ff920faec6ee06e17212e2b5d2ee117495e87 (patch)
treef9e11076efc093b3370e559bd9ec0e5475e982a2 /mllib
parent38cdd6ccdaba7f8da985c4f4efe5bd93a46a2b53 (diff)
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[SPARK-17748][FOLLOW-UP][ML] Fix build error for Scala 2.10.
## What changes were proposed in this pull request? #15394 introduced build error for Scala 2.10, this PR fix it. ## How was this patch tested? Existing test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #15625 from yanboliang/spark-17748-scala.
Diffstat (limited to 'mllib')
-rw-r--r--mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala13
1 files 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 5f638b4880..3cdab03279 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)