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apache · Nov 3, 2015 · 29a8067 · 29a8067
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commit 29a8067
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Showing 8 changed files with 16 additions and 9 deletions.
diff --git a/examples/src/main/python/mllib/gradient_boosting_classification_example.py b/examples/src/main/python/mllib/gradient_boosting_classification_example.py
@@ -27,7 +27,9 @@
 from pyspark.mllib.tree import GradientBoostedTrees, GradientBoostedTreesModel
 from pyspark.mllib.util import MLUtils
 # $example off$
+
 if __name__ == "__main__":
+    sc = SparkContext(appName="PythonGradientBoostedTreesClassificationExample")
     # $example on$
     # Load and parse the data file.
     data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt")

diff --git a/examples/src/main/python/mllib/gradient_boosting_regression_example.py b/examples/src/main/python/mllib/gradient_boosting_regression_example.py
@@ -27,8 +27,9 @@
 from pyspark.mllib.tree import GradientBoostedTrees, GradientBoostedTreesModel
 from pyspark.mllib.util import MLUtils
 # $example off$
-# $example off#
+
 if __name__ == "__main__":
+    sc = SparkContext(appName="PythonGradientBoostedTreesRegressionExample")
     # $example on$
     # Load and parse the data file.
     data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt")
@@ -44,8 +45,8 @@
     # 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() /
-    float(testData.count())
+    testMSE = labelsAndPredictions.map(lambda (v, p): (v - p) * (v - p)).sum() /\
+        float(testData.count())
     print('Test Mean Squared Error = ' + str(testMSE))
     print('Learned regression GBT model:')
     print(model.toDebugString())

diff --git a/examples/src/main/python/mllib/random_forest_classification_example.py b/examples/src/main/python/mllib/random_forest_classification_example.py
@@ -27,7 +27,9 @@
 from pyspark.mllib.tree import RandomForest, RandomForestModel
 from pyspark.mllib.util import MLUtils
 # $example off$
+
 if __name__ == "__main__":
+    sc = SparkContext(appName="PythonRandomForestClassificationExample")
     # $example on$
     # Load and parse the data file into an RDD of LabeledPoint.
     data = MLUtils.loadLibSVMFile(sc, 'data/mllib/sample_libsvm_data.txt')

diff --git a/examples/src/main/python/mllib/random_forest_regression_example.py b/examples/src/main/python/mllib/random_forest_regression_example.py
@@ -27,7 +27,9 @@
 from pyspark.mllib.tree import RandomForest, RandomForestModel
 from pyspark.mllib.util import MLUtils
 # $example off$
+
 if __name__ == "__main__":
+    sc = SparkContext(appName="PythonRandomForestRegressionExample")
     # $example on$
     # Load and parse the data file into an RDD of LabeledPoint.
     data = MLUtils.loadLibSVMFile(sc, 'data/mllib/sample_libsvm_data.txt')
@@ -45,8 +47,8 @@
     # 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() /
-    float(testData.count())
+    testMSE = labelsAndPredictions.map(lambda (v, p): (v - p) * (v - p)).sum() /\
+        float(testData.count())
     print('Test Mean Squared Error = ' + str(testMSE))
     print('Learned regression forest model:')
     print(model.toDebugString())

diff --git a/...rc/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala b/...rc/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
@@ -27,7 +27,7 @@ import org.apache.spark.mllib.util.MLUtils
 // $example off$
 
 object GradientBoostingClassificationExample {
-  def main(args: Array[String]) {
+  def main(args: Array[String]): Unit = {
     val conf = new SparkConf().setAppName("GradientBoostedTreesClassificationExample")
     val sc = new SparkContext(conf)
     // $example on$

diff --git a/...es/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingRegressionExample.scala b/...es/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingRegressionExample.scala
@@ -27,7 +27,7 @@ import org.apache.spark.mllib.util.MLUtils
 // $example off$
 
 object GradientBoostingRegressionExample {
-  def main(args: Array[String]) {
+  def main(args: Array[String]): Unit = {
     val conf = new SparkConf().setAppName("GradientBoostedTreesRegressionExample")
     val sc = new SparkContext(conf)
     // $example on$

diff --git a/...es/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala b/...es/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
@@ -26,7 +26,7 @@ import org.apache.spark.mllib.util.MLUtils
 // $example off$
 
 object RandomForestClassificationExample {
-  def main(args: Array[String]) {
+  def main(args: Array[String]): Unit = {
     val conf = new SparkConf().setAppName("RandomForestClassificationExample")
     val sc = new SparkContext(conf)
     // $example on$

diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala
@@ -26,7 +26,7 @@ import org.apache.spark.mllib.util.MLUtils
 // $example off$
 
 object RandomForestRegressionExample {
-  def main(args: Array[String]) {
+  def main(args: Array[String]): Unit = {
     val conf = new SparkConf().setAppName("RandomForestRegressionExample")
     val sc = new SparkContext(conf)
     // $example on$