Package io.prediction.examples.java.recommendations.tutorial1

Examples of io.prediction.examples.java.recommendations.tutorial1.TrainingData$Rating

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  }

  public static void runComponents(String filePath) {
    JavaEngineParams engineParams = new JavaEngineParamsBuilder()
      .dataSourceParams(new DataSourceParams(filePath))
      .addAlgorithmParams("MyRecommendationAlgo", new AlgoParams(0.2)) // Add Algorithm Params
      .build();

    JavaWorkflow.runEngine(
      (new HalfBakedEngineFactory()).apply(),
      engineParams,
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public class Runner3 {

  public static void runEvaluation(String filePath) {
    JavaEngineParams engineParams = new JavaEngineParamsBuilder()
      .dataSourceParams(new DataSourceParams(filePath))
      .addAlgorithmParams("MyRecommendationAlgo", new AlgoParams(0.2))
      .build();

    JavaWorkflow.runEngine(
      (new EngineFactory()).apply(),
      engineParams,
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public class Runner5 {

  public static void runEvaluation(String filePath) {
    JavaEngineParams engineParams = new JavaEngineParamsBuilder()
      .dataSourceParams(new DataSourceParams(filePath))
      .addAlgorithmParams("MyMahoutRecommendationAlgo",
        new MahoutAlgoParams("LogLikelihoodSimilarity"))
      .build();

    JavaWorkflow.runEngine(
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    }
  }

  public static void runComponents(String filePath) {
    JavaEngineParams engineParams = new JavaEngineParamsBuilder()
      .dataSourceParams(new DataSourceParams(filePath))
      .build();

    JavaWorkflow.runEngine(
      (new HalfBakedEngineFactory()).apply(),
      engineParams,
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    }
  }

  public static void runComponents(String filePath) {
    JavaEngineParams engineParams = new JavaEngineParamsBuilder()
      .dataSourceParams(new DataSourceParams(filePath))
      .addAlgorithmParams("MyRecommendationAlgo", new AlgoParams(0.2)) // Add Algorithm Params
      .build();

    JavaWorkflow.runEngine(
      (new HalfBakedEngineFactory()).apply(),
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public class Runner3 {

  public static void runEvaluation(String filePath) {
    JavaEngineParams engineParams = new JavaEngineParamsBuilder()
      .dataSourceParams(new DataSourceParams(filePath))
      .addAlgorithmParams("MyRecommendationAlgo", new AlgoParams(0.2))
      .build();

    JavaWorkflow.runEngine(
      (new EngineFactory()).apply(),
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  private List<Tuple2<Query, Float>> prepareValidation(List<TrainingData.Rating> testRatings) {
    List<Tuple2<Query, Float>> validationList = new ArrayList<Tuple2<Query, Float>>();

    for (TrainingData.Rating r : testRatings) {
      validationList.add(new Tuple2<Query, Float>(
        new Query(r.uid, r.iid),
        r.rating));
    }

    return validationList;
  }
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      // create a new ArrayList because subList() returns view and not serialzable
      List<TrainingData.Rating> trainingRatings =
        new ArrayList<TrainingData.Rating>(ratings.subList(0, trainingEndIndex));
      List<TrainingData.Rating> testRatings = ratings.subList(trainingEndIndex, testEndIndex);
      TrainingData td = new TrainingData(trainingRatings);
      List<Tuple2<Query, Float>> qaList = prepareValidation(testRatings);

      data.add(new Tuple3<Object, TrainingData, Iterable<Tuple2<Query, Float>>>(
        null, td, qaList));
    }
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Related Classes of io.prediction.examples.java.recommendations.tutorial1.TrainingData$Rating

  • io.prediction.examples.java.recommendations.tutorial2.Runner1
  • io.prediction.examples.java.recommendations.tutorial2.Runner2
  • io.prediction.examples.java.recommendations.tutorial3.DataSource
  • io.prediction.examples.java.recommendations.tutorial3.Runner3
  • io.prediction.examples.java.recommendations.tutorial5.Runner5
  • org.apache.commons.math3.linear.ArrayRealVector
  • org.apache.commons.math3.linear.OpenMapRealVector
  • org.apache.commons.math3.linear.RealVector
  • java.io.File
  • java.util.Scanner
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