1 files changed, 4 insertions, 3 deletions
diff --git a/examples/src/main/python/mllib/gradient_boosted_trees.py b/examples/src/main/python/mllib/gradient_boosted_trees.py
index e647773ad9..781bd61c9d 100644
--- a/examples/src/main/python/mllib/gradient_boosted_trees.py
+++ b/examples/src/main/python/mllib/gradient_boosted_trees.py
@@ -18,6 +18,7 @@
 """
 Gradient boosted Trees classification and regression using MLlib.
 """
+from __future__ import print_function
 
 import sys
 
@@ -34,7 +35,7 @@ def testClassification(trainingData, testData):
     # Evaluate model on test instances and compute test error
     predictions = model.predict(testData.map(lambda x: x.features))
     labelsAndPredictions = testData.map(lambda lp: lp.label).zip(predictions)
-    testErr = labelsAndPredictions.filter(lambda (v, p): v != p).count() \
+    testErr = labelsAndPredictions.filter(lambda v_p: v_p[0] != v_p[1]).count() \
         / float(testData.count())
     print('Test Error = ' + str(testErr))
     print('Learned classification ensemble model:')
@@ -49,7 +50,7 @@ def testRegression(trainingData, testData):
     # Evaluate model on test instances and compute test error
     predictions = model.predict(testData.map(lambda x: x.features))
     labelsAndPredictions = testData.map(lambda lp: lp.label).zip(predictions)
-    testMSE = labelsAndPredictions.map(lambda (v, p): (v - p) * (v - p)).sum() \
+    testMSE = labelsAndPredictions.map(lambda vp: (vp[0] - vp[1]) * (vp[0] - vp[1])).sum() \
         / float(testData.count())
     print('Test Mean Squared Error = ' + str(testMSE))
     print('Learned regression ensemble model:')
@@ -58,7 +59,7 @@ def testRegression(trainingData, testData):
 
 if __name__ == "__main__":
     if len(sys.argv) > 1:
-        print >> sys.stderr, "Usage: gradient_boosted_trees"
+        print("Usage: gradient_boosted_trees", file=sys.stderr)
         exit(1)
     sc = SparkContext(appName="PythonGradientBoostedTrees")