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[SPARK-11445][DOCS]Replaced example code in mllib-ensembles.md using include_example #9407

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[SPARK-11445][DOCS]Replaced example code in mllib-ensembles.md using include_example #9407

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[ SPARK-11180 ] [ SQL ] DataFrame.na.fill does not support Boolean Type
rishabhbhardwaj Oct 19, 2015
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Merge remote-tracking branch 'upstream/master'
rishabhbhardwaj Oct 20, 2015
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rishabhbhardwaj Oct 26, 2015
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rishabhbhardwaj Oct 29, 2015
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rishabhbhardwaj Nov 2, 2015
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[SPARK-11445] [DOCS] Replace example code in mllib-ensembles.md using…
rishabhbhardwaj Nov 2, 2015
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code style changes
rishabhbhardwaj Nov 3, 2015
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rishabhbhardwaj Nov 3, 2015
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rishabhbhardwaj committed Nov 3, 2015
commit 29a8067cee1ef3f047ff3e2248de812f3e1453fb
2 changes: 2 additions & 0 deletions examples/src/main/python/mllib/gradient_boosting_classification_example.py
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Expand Up @@ -27,7 +27,9 @@
from pyspark.mllib.tree import GradientBoostedTrees, GradientBoostedTreesModel
from pyspark.mllib.util import MLUtils
# $example off$
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@yinxusen yinxusen Nov 3, 2015

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blank line


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")
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7 changes: 4 additions & 3 deletions examples/src/main/python/mllib/gradient_boosting_regression_example.py
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Expand Up @@ -27,8 +27,9 @@
from pyspark.mllib.tree import GradientBoostedTrees, GradientBoostedTreesModel
from pyspark.mllib.util import MLUtils
# $example off$
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@yinxusen yinxusen Nov 3, 2015

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duplicated 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")
Expand All @@ -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())
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2 changes: 2 additions & 0 deletions examples/src/main/python/mllib/random_forest_classification_example.py
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Expand Up @@ -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')
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6 changes: 4 additions & 2 deletions examples/src/main/python/mllib/random_forest_regression_example.py
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Expand Up @@ -27,7 +27,9 @@
from pyspark.mllib.tree import RandomForest, RandomForestModel
from pyspark.mllib.util import MLUtils
# $example off$
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@yinxusen yinxusen Nov 3, 2015

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blank line here


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')
Expand All @@ -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())
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2 changes: 1 addition & 1 deletion ...rc/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
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Expand Up @@ -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)
// $example on$
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2 changes: 1 addition & 1 deletion ...es/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingRegressionExample.scala
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Expand Up @@ -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)
// $example on$
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2 changes: 1 addition & 1 deletion ...es/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
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Expand Up @@ -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)
// $example on$
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2 changes: 1 addition & 1 deletion examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala
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Expand Up @@ -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)
// $example on$
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