1 files changed, 0 insertions, 82 deletions
diff --git a/examples/src/main/java/org/apache/spark/examples/mllib/JavaLR.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaLR.java
deleted file mode 100644
index eceb6927d5..0000000000
--- a/examples/src/main/java/org/apache/spark/examples/mllib/JavaLR.java
+++ /dev/null
@@ -1,82 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *    http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.spark.examples.mllib;
-
-import java.util.regex.Pattern;
-
-import org.apache.spark.SparkConf;
-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;
-
-/**
- * Logistic regression based classification using ML Lib.
- */
-public final class JavaLR {
-
-  static class ParsePoint implements Function<String, LabeledPoint> {
-    private static final Pattern COMMA = Pattern.compile(",");
-    private static final Pattern SPACE = Pattern.compile(" ");
-
-    @Override
-    public LabeledPoint call(String line) {
-      String[] parts = COMMA.split(line);
-      double y = Double.parseDouble(parts[0]);
-      String[] tok = SPACE.split(parts[1]);
-      double[] x = new double[tok.length];
-      for (int i = 0; i < tok.length; ++i) {
-        x[i] = Double.parseDouble(tok[i]);
-      }
-      return new LabeledPoint(y, Vectors.dense(x));
-    }
-  }
-
-  public static void main(String[] args) {
-    if (args.length != 3) {
-      System.err.println("Usage: JavaLR <input_dir> <step_size> <niters>");
-      System.exit(1);
-    }
-    SparkConf sparkConf = new SparkConf().setAppName("JavaLR");
-    JavaSparkContext sc = new JavaSparkContext(sparkConf);
-    JavaRDD<String> lines = sc.textFile(args[0]);
-    JavaRDD<LabeledPoint> points = lines.map(new ParsePoint()).cache();
-    double stepSize = Double.parseDouble(args[1]);
-    int iterations = Integer.parseInt(args[2]);
-
-    // Another way to configure LogisticRegression
-    //
-    // LogisticRegressionWithSGD lr = new LogisticRegressionWithSGD();
-    // lr.optimizer().setNumIterations(iterations)
-    //               .setStepSize(stepSize)
-    //               .setMiniBatchFraction(1.0);
-    // lr.setIntercept(true);
-    // LogisticRegressionModel model = lr.train(points.rdd());
-
-    LogisticRegressionModel model = LogisticRegressionWithSGD.train(points.rdd(),
-      iterations, stepSize);
-
-    System.out.print("Final w: " + model.weights());
-
-    sc.stop();
-  }
-}