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[SPARK-11383][DOCS] Replaced example code in mllib-naive-bayes.md/mll…
…ib-isotonic-regression.md using include_example I have made the required changes in mllib-naive-bayes.md/mllib-isotonic-regression.md and also verified them. Kindle Review it. Author: Rishabh Bhardwaj <rbnext29@gmail.com> Closes #9353 from rishabhbhardwaj/SPARK-11383.
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examples/src/main/java/org/apache/spark/examples/mllib/JavaIsotonicRegressionExample.java
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| /* | ||
| * 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; | ||
|
|
||
| // $example on$ | ||
| import scala.Tuple2; | ||
| import scala.Tuple3; | ||
| import org.apache.spark.api.java.function.Function; | ||
| import org.apache.spark.api.java.function.PairFunction; | ||
| import org.apache.spark.api.java.JavaDoubleRDD; | ||
| import org.apache.spark.api.java.JavaPairRDD; | ||
| import org.apache.spark.api.java.JavaSparkContext; | ||
| import org.apache.spark.api.java.JavaRDD; | ||
| import org.apache.spark.mllib.regression.IsotonicRegression; | ||
| import org.apache.spark.mllib.regression.IsotonicRegressionModel; | ||
| // $example off$ | ||
| import org.apache.spark.SparkConf; | ||
|
|
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| public class JavaIsotonicRegressionExample { | ||
| public static void main(String[] args) { | ||
| SparkConf sparkConf = new SparkConf().setAppName("JavaIsotonicRegressionExample"); | ||
| JavaSparkContext jsc = new JavaSparkContext(sparkConf); | ||
| // $example on$ | ||
| JavaRDD<String> data = jsc.textFile("data/mllib/sample_isotonic_regression_data.txt"); | ||
|
|
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| // Create label, feature, weight tuples from input data with weight set to default value 1.0. | ||
| JavaRDD<Tuple3<Double, Double, Double>> parsedData = data.map( | ||
| new Function<String, Tuple3<Double, Double, Double>>() { | ||
| public Tuple3<Double, Double, Double> call(String line) { | ||
| String[] parts = line.split(","); | ||
| return new Tuple3<>(new Double(parts[0]), new Double(parts[1]), 1.0); | ||
| } | ||
| } | ||
| ); | ||
|
|
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| // Split data into training (60%) and test (40%) sets. | ||
| JavaRDD<Tuple3<Double, Double, Double>>[] splits = parsedData.randomSplit(new double[]{0.6, 0.4}, 11L); | ||
| JavaRDD<Tuple3<Double, Double, Double>> training = splits[0]; | ||
| JavaRDD<Tuple3<Double, Double, Double>> test = splits[1]; | ||
|
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| // Create isotonic regression model from training data. | ||
| // Isotonic parameter defaults to true so it is only shown for demonstration | ||
| final IsotonicRegressionModel model = new IsotonicRegression().setIsotonic(true).run(training); | ||
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| // Create tuples of predicted and real labels. | ||
| JavaPairRDD<Double, Double> predictionAndLabel = test.mapToPair( | ||
| new PairFunction<Tuple3<Double, Double, Double>, Double, Double>() { | ||
| @Override | ||
| public Tuple2<Double, Double> call(Tuple3<Double, Double, Double> point) { | ||
| Double predictedLabel = model.predict(point._2()); | ||
| return new Tuple2<Double, Double>(predictedLabel, point._1()); | ||
| } | ||
| } | ||
| ); | ||
|
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| // Calculate mean squared error between predicted and real labels. | ||
| Double meanSquaredError = new JavaDoubleRDD(predictionAndLabel.map( | ||
| new Function<Tuple2<Double, Double>, Object>() { | ||
| @Override | ||
| public Object call(Tuple2<Double, Double> pl) { | ||
| return Math.pow(pl._1() - pl._2(), 2); | ||
| } | ||
| } | ||
| ).rdd()).mean(); | ||
| System.out.println("Mean Squared Error = " + meanSquaredError); | ||
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| // Save and load model | ||
| model.save(jsc.sc(), "target/tmp/myIsotonicRegressionModel"); | ||
| IsotonicRegressionModel sameModel = IsotonicRegressionModel.load(jsc.sc(), "target/tmp/myIsotonicRegressionModel"); | ||
| // $example off$ | ||
| } | ||
| } |
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