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 4e812994405b329ee7984ebc0b1b358ca86e6fa9..94b0e00f37267a064b23b68aa28d86bca5a3c003 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
@@ -178,15 +178,16 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext with M
     // Use half as many iterations as the previous test.
     val lr = new LogisticRegressionWithSGD().setIntercept(true)
     lr.optimizer.
-      setStepSize(10.0).
+      setStepSize(1.0).
       setNumIterations(10).
       setRegParam(1.0)
 
     val model = lr.run(testRDD, initialWeights)
 
     // Test the weights
-    assert(model.weights(0) ~== -430000.0 relTol 20000.0)
-    assert(model.intercept ~== 370000.0 relTol 20000.0)
+    // With regularization, the resulting weights will be smaller.
+    assert(model.weights(0) ~== -0.14 relTol 0.02)
+    assert(model.intercept ~== 0.25 relTol 0.02)
 
     val validationData = LogisticRegressionSuite.generateLogisticInput(A, B, nPoints, 17)
     val validationRDD = sc.parallelize(validationData, 2)