Fixing typos in Java tests, and addressing alignment issues.

4 files changed, 16 insertions, 16 deletions

diff --git a/mllib/src/main/scala/spark/mllib/util/LinearDataGenerator.scala b/mllib/src/main/scala/spark/mllib/util/LinearDataGenerator.scala
index 8fe3ab4754..20e1656beb 100644
--- a/mllib/src/main/scala/spark/mllib/util/LinearDataGenerator.scala
+++ b/mllib/src/main/scala/spark/mllib/util/LinearDataGenerator.scala
@@ -91,13 +91,13 @@ object LinearDataGenerator {
    * @return RDD of LabeledPoint containing sample data.
    */
   def generateLinearRDD(
-    sc: SparkContext,
-    nexamples: Int,
-    nfeatures: Int,
-    eps: Double,
-    weights: Array[Double] = Array[Double](),
-    nparts: Int = 2,
-    intercept: Double = 0.0) : RDD[LabeledPoint] = {
+      sc: SparkContext,
+      nexamples: Int,
+      nfeatures: Int,
+      eps: Double,
+      weights: Array[Double] = Array[Double](),
+      nparts: Int = 2,
+      intercept: Double = 0.0) : RDD[LabeledPoint] = {
     org.jblas.util.Random.seed(42)
     // Random values distributed uniformly in [-0.5, 0.5]
     val w = DoubleMatrix.rand(nfeatures, 1).subi(0.5)
diff --git a/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java b/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java
index 8d692c2d0d..428902e85c 100644
--- a/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java
+++ b/mllib/src/test/java/spark/mllib/regression/JavaLassoSuite.java
@@ -67,11 +67,11 @@ public class JavaLassoSuite implements Serializable {
     List<LabeledPoint> validationData =
         LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
-    LassoWithSGD svmSGDImpl = new LassoWithSGD();
-    svmSGDImpl.optimizer().setStepSize(1.0)
+    LassoWithSGD lassoSGDImpl = new LassoWithSGD();
+    lassoSGDImpl.optimizer().setStepSize(1.0)
                           .setRegParam(0.01)
                           .setNumIterations(20);
-    LassoModel model = svmSGDImpl.run(testRDD.rdd());
+    LassoModel model = lassoSGDImpl.run(testRDD.rdd());
 
     int numAccurate = validatePrediction(validationData, model);
     Assert.assertTrue(numAccurate > nPoints * 4.0 / 5.0);
diff --git a/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java b/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java
index d2d8a62980..9642e89844 100644
--- a/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java
+++ b/mllib/src/test/java/spark/mllib/regression/JavaLinearRegressionSuite.java
@@ -67,11 +67,11 @@ public class JavaLinearRegressionSuite implements Serializable {
         List<LabeledPoint> validationData =
                 LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
-        LinearRegressionWithSGD svmSGDImpl = new LinearRegressionWithSGD();
-        svmSGDImpl.optimizer().setStepSize(1.0)
+        LinearRegressionWithSGD linSGDImpl = new LinearRegressionWithSGD();
+        linSGDImpl.optimizer().setStepSize(1.0)
                 .setRegParam(0.01)
                 .setNumIterations(20);
-        LinearRegressionModel model = svmSGDImpl.run(testRDD.rdd());
+        LinearRegressionModel model = linSGDImpl.run(testRDD.rdd());
 
         int numAccurate = validatePrediction(validationData, model);
         Assert.assertTrue(numAccurate > nPoints * 4.0 / 5.0);
diff --git a/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java b/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java
index 72ab875985..5df6d8076d 100644
--- a/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java
+++ b/mllib/src/test/java/spark/mllib/regression/JavaRidgeRegressionSuite.java
@@ -67,11 +67,11 @@ public class JavaRidgeRegressionSuite implements Serializable {
         List<LabeledPoint> validationData =
                 LinearDataGenerator.generateLinearInputAsList(A, weights, nPoints, 17);
 
-        RidgeRegressionWithSGD svmSGDImpl = new RidgeRegressionWithSGD();
-        svmSGDImpl.optimizer().setStepSize(1.0)
+        RidgeRegressionWithSGD ridgeSGDImpl = new RidgeRegressionWithSGD();
+        ridgeSGDImpl.optimizer().setStepSize(1.0)
                 .setRegParam(0.01)
                 .setNumIterations(20);
-        RidgeRegressionModel model = svmSGDImpl.run(testRDD.rdd());
+        RidgeRegressionModel model = ridgeSGDImpl.run(testRDD.rdd());
 
         int numAccurate = validatePrediction(validationData, model);
         Assert.assertTrue(numAccurate > nPoints * 4.0 / 5.0);