update JavaLR example

Author: mengxr

examples/src/main/java/org/apache/spark/mllib/examples/JavaLR.java

@@ -17,18 +17,17 @@
 
 package org.apache.spark.mllib.examples;
 
+import java.util.regex.Pattern;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.api.java.function.Function;
 
 import org.apache.spark.mllib.classification.LogisticRegressionWithSGD;
 import org.apache.spark.mllib.classification.LogisticRegressionModel;
+import org.apache.spark.mllib.linalg.Vectors;
 import org.apache.spark.mllib.regression.LabeledPoint;
 
-import java.util.Arrays;
-import java.util.regex.Pattern;
-
 /**
  * Logistic regression based classification using ML Lib.
  */
@@ -47,14 +46,10 @@ public LabeledPoint call(String line) {
       for (int i = 0; i < tok.length; ++i) {
         x[i] = Double.parseDouble(tok[i]);
       }
-      return new LabeledPoint(y, x);
+      return new LabeledPoint(y, Vectors.dense(x));
     }
   }
 
-  public static void printWeights(double[] a) {
-    System.out.println(Arrays.toString(a));
-  }
-
   public static void main(String[] args) {
     if (args.length != 4) {
       System.err.println("Usage: JavaLR <master> <input_dir> <step_size> <niters>");
@@ -80,8 +75,7 @@ public static void main(String[] args) {
     LogisticRegressionModel model = LogisticRegressionWithSGD.train(points.rdd(),
         iterations, stepSize);
 
-    System.out.print("Final w: ");
-    printWeights(model.weights());
+    System.out.print("Final w: " + model.weights());
 
     System.exit(0);
   }