Changes as per comments in PR #8377.

apache · Aug 27, 2015 · 1dd1cd1 · 1dd1cd1
1 parent 6443d55
commit 1dd1cd1
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Showing 2 changed files with 23 additions and 4 deletions.
diff --git a/docs/ml-guide.md b/docs/ml-guide.md
@@ -888,6 +888,13 @@ The `ParamMap` which produces the best evaluation metric is selected as the best
 
 <div data-lang="scala" markdown="1">
 {% highlight scala %}
+import org.apache.spark.ml.evaluation.RegressionEvaluator
+import org.apache.spark.ml.regression.LinearRegression
+import org.apache.spark.ml.tuning.{ParamGridBuilder, TrainValidationSplit}
+import org.apache.spark.mllib.util.MLUtils
+import org.apache.spark.sql.SQLContext
+import org.apache.spark.{SparkConf, SparkContext}
+
 import sqlContext.implicits._
 
 // Prepare training and test data.
@@ -931,6 +938,18 @@ sc.stop()
 
 <div data-lang="java" markdown="1">
 {% highlight java %}
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.evaluation.RegressionEvaluator;
+import org.apache.spark.ml.param.ParamMap;
+import org.apache.spark.ml.regression.LinearRegression;
+import org.apache.spark.ml.tuning.*;
+import org.apache.spark.mllib.regression.LabeledPoint;
+import org.apache.spark.mllib.util.MLUtils;
+import org.apache.spark.rdd.RDD;
+import org.apache.spark.sql.DataFrame;
+import org.apache.spark.sql.SQLContext;
+
 RDD<LabeledPoint> data = MLUtils.loadLibSVMFile(jsc.sc(), "data/mllib/sample_libsvm_data.txt");
 RDD<LabeledPoint>[] splits = data.randomSplit(new double []{0.9, 0.1}, 12345);
 

diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaTrainValidationSplitExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaTrainValidationSplitExample.java
@@ -43,12 +43,12 @@
 public class JavaTrainValidationSplitExample {
 
   public static void main(String[] args) {
-    SparkConf conf = new SparkConf().setAppName("JavaTrainValidationSplitExample").setMaster("local[2]");
+    SparkConf conf = new SparkConf().setAppName("JavaTrainValidationSplitExample");
     JavaSparkContext jsc = new JavaSparkContext(conf);
     SQLContext jsql = new SQLContext(jsc);
 
     RDD<LabeledPoint> data = MLUtils.loadLibSVMFile(jsc.sc(), "data/mllib/sample_libsvm_data.txt");
-    RDD<LabeledPoint>[] splits = data.randomSplit(new double []{0.9, 0.1}, 12345);
+    RDD<LabeledPoint>[] splits = data.randomSplit(new double [] {0.9, 0.1}, 12345);
 
     // Prepare training and test data.
     DataFrame training = jsql.createDataFrame(splits[0], LabeledPoint.class);
@@ -66,9 +66,9 @@ public static void main(String[] args) {
     // TrainValidationSplit will try all combinations of values and determine best model using
     // the evaluator.
     ParamMap[] paramGrid = new ParamGridBuilder()
-      .addGrid(lr.regParam(), new double[]{0.1, 0.01})
+      .addGrid(lr.regParam(), new double[] {0.1, 0.01})
       .addGrid(lr.fitIntercept())
-      .addGrid(lr.elasticNetParam(), new double[]{0.0, 0.5, 1.0})
+      .addGrid(lr.elasticNetParam(), new double[] {0.0, 0.5, 1.0})
       .build();
 
     trainValidationSplit.setEstimatorParamMaps(paramGrid);