diff options
Diffstat (limited to 'mllib/src/test/scala')
| -rw-r--r-- | mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala index d140545e37..cea0adc55c 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala @@ -667,9 +667,9 @@ class LogisticRegressionSuite extends SparkFunSuite with MLlibTestSparkContext w test("binary logistic regression with intercept with L1 regularization") { val trainer1 = new LogisticRegressionWithLBFGS().setIntercept(true).setFeatureScaling(true) - trainer1.optimizer.setUpdater(new L1Updater).setRegParam(0.12).setConvergenceTol(1E-6) + trainer1.optimizer.setUpdater(new L1Updater).setRegParam(0.12) val trainer2 = new LogisticRegressionWithLBFGS().setIntercept(true).setFeatureScaling(false) - trainer2.optimizer.setUpdater(new L1Updater).setRegParam(0.12).setConvergenceTol(1E-6) + trainer2.optimizer.setUpdater(new L1Updater).setRegParam(0.12) val model1 = trainer1.run(binaryDataset) val model2 = trainer2.run(binaryDataset) @@ -726,9 +726,9 @@ class LogisticRegressionSuite extends SparkFunSuite with MLlibTestSparkContext w test("binary logistic regression without intercept with L1 regularization") { val trainer1 = new LogisticRegressionWithLBFGS().setIntercept(false).setFeatureScaling(true) - trainer1.optimizer.setUpdater(new L1Updater).setRegParam(0.12).setConvergenceTol(1E-6) + trainer1.optimizer.setUpdater(new L1Updater).setRegParam(0.12) val trainer2 = new LogisticRegressionWithLBFGS().setIntercept(false).setFeatureScaling(false) - trainer2.optimizer.setUpdater(new L1Updater).setRegParam(0.12).setConvergenceTol(1E-6) + trainer2.optimizer.setUpdater(new L1Updater).setRegParam(0.12) val model1 = trainer1.run(binaryDataset) val model2 = trainer2.run(binaryDataset) @@ -786,9 +786,9 @@ class LogisticRegressionSuite extends SparkFunSuite with MLlibTestSparkContext w test("binary logistic regression with intercept with L2 regularization") { val trainer1 = new LogisticRegressionWithLBFGS().setIntercept(true).setFeatureScaling(true) - trainer1.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37).setConvergenceTol(1E-6) + trainer1.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37) val trainer2 = new LogisticRegressionWithLBFGS().setIntercept(true).setFeatureScaling(false) - trainer2.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37).setConvergenceTol(1E-6) + trainer2.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37) val model1 = trainer1.run(binaryDataset) val model2 = trainer2.run(binaryDataset) @@ -845,9 +845,9 @@ class LogisticRegressionSuite extends SparkFunSuite with MLlibTestSparkContext w test("binary logistic regression without intercept with L2 regularization") { val trainer1 = new LogisticRegressionWithLBFGS().setIntercept(false).setFeatureScaling(true) - trainer1.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37).setConvergenceTol(1E-6) + trainer1.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37) val trainer2 = new LogisticRegressionWithLBFGS().setIntercept(false).setFeatureScaling(false) - trainer2.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37).setConvergenceTol(1E-6) + trainer2.optimizer.setUpdater(new SquaredL2Updater).setRegParam(1.37) val model1 = trainer1.run(binaryDataset) val model2 = trainer2.run(binaryDataset) |