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diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.tree.impl
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.internal.Logging
+import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.tree.{GradientBoostedTreesSuite => OldGBTSuite}
+import org.apache.spark.mllib.tree.configuration.{BoostingStrategy, Strategy}
+import org.apache.spark.mllib.tree.configuration.Algo._
+import org.apache.spark.mllib.tree.impurity.Variance
+import org.apache.spark.mllib.tree.loss.{AbsoluteError, LogLoss, SquaredError}
+import org.apache.spark.mllib.util.MLlibTestSparkContext
+
+/**
+ * Test suite for [[GradientBoostedTrees]].
+ */
+class GradientBoostedTreesSuite extends SparkFunSuite with MLlibTestSparkContext with Logging {
+
+  test("runWithValidation stops early and performs better on a validation dataset") {
+    // Set numIterations large enough so that it stops early.
+    val numIterations = 20
+    val trainRdd = sc.parallelize(OldGBTSuite.trainData, 2)
+    val validateRdd = sc.parallelize(OldGBTSuite.validateData, 2)
+    val trainDF = sqlContext.createDataFrame(trainRdd)
+    val validateDF = sqlContext.createDataFrame(validateRdd)
+
+    val algos = Array(Regression, Regression, Classification)
+    val losses = Array(SquaredError, AbsoluteError, LogLoss)
+    algos.zip(losses).foreach { case (algo, loss) =>
+      val treeStrategy = new Strategy(algo = algo, impurity = Variance, maxDepth = 2,
+        categoricalFeaturesInfo = Map.empty)
+      val boostingStrategy =
+        new BoostingStrategy(treeStrategy, loss, numIterations, validationTol = 0.0)
+      val (validateTrees, validateTreeWeights) = GradientBoostedTrees
+        .runWithValidation(trainRdd, validateRdd, boostingStrategy, 42L)
+      val numTrees = validateTrees.length
+      assert(numTrees !== numIterations)
+
+      // Test that it performs better on the validation dataset.
+      val (trees, treeWeights) = GradientBoostedTrees.run(trainRdd, boostingStrategy, 42L)
+      val (errorWithoutValidation, errorWithValidation) = {
+        if (algo == Classification) {
+          val remappedRdd = validateRdd.map(x => new LabeledPoint(2 * x.label - 1, x.features))
+          (GradientBoostedTrees.computeError(remappedRdd, trees, treeWeights, loss),
+            GradientBoostedTrees.computeError(remappedRdd, validateTrees,
+              validateTreeWeights, loss))
+        } else {
+          (GradientBoostedTrees.computeError(validateRdd, trees, treeWeights, loss),
+            GradientBoostedTrees.computeError(validateRdd, validateTrees,
+              validateTreeWeights, loss))
+        }
+      }
+      assert(errorWithValidation <= errorWithoutValidation)
+
+      // Test that results from evaluateEachIteration comply with runWithValidation.
+      // Note that convergenceTol is set to 0.0
+      val evaluationArray = GradientBoostedTrees
+        .evaluateEachIteration(validateRdd, trees, treeWeights, loss, algo)
+      assert(evaluationArray.length === numIterations)
+      assert(evaluationArray(numTrees) > evaluationArray(numTrees - 1))
+      var i = 1
+      while (i < numTrees) {
+        assert(evaluationArray(i) <= evaluationArray(i - 1))
+        i += 1
+      }
+    }
+  }
+
+}