Examples of writeToSeqFiles()

Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    }
   
    Path priorClustersPath = new Path(output, Cluster.INITIAL_CLUSTERS_DIR);
    ClusteringPolicy policy = new KMeansClusteringPolicy(convergenceDelta);
    ClusterClassifier prior = new ClusterClassifier(clusters, policy);
    prior.writeToSeqFiles(priorClustersPath);
   
    if (runSequential) {
      ClusterIterator.iterateSeq(conf, input, priorClustersPath, output, maxIterations);
    } else {
      ClusterIterator.iterateMR(conf, input, priorClustersPath, output, maxIterations);
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    }
   
    Path priorClustersPath = new Path(output, Cluster.INITIAL_CLUSTERS_DIR);  
    ClusteringPolicy policy = new FuzzyKMeansClusteringPolicy(m, convergenceDelta);
    ClusterClassifier prior = new ClusterClassifier(clusters, policy);
    prior.writeToSeqFiles(priorClustersPath);
   
    if (runSequential) {
      ClusterIterator.iterateSeq(conf, input, priorClustersPath, output, maxIterations);
    } else {
      ClusterIterator.iterateMR(conf, input, priorClustersPath, output, maxIterations);
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    for (Model<VectorWritable> cluster : modelDist.sampleFromPrior(numClusters)) {
      models.add((Cluster) cluster);
    }
   
    ClusterClassifier prior = new ClusterClassifier(models, new DirichletClusteringPolicy(numClusters, alpha0));
    prior.writeToSeqFiles(clustersIn);
   
    if (runSequential) {
      ClusterIterator.iterateSeq(conf, input, clustersIn, output, maxIterations);
    } else {
      ClusterIterator.iterateMR(conf, input, clustersIn, output, maxIterations);
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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      classifier.close();
      // update the policy
      classifier.getPolicy().update(classifier);
      // output the classifier
      clustersOut = new Path(outPath, Cluster.CLUSTERS_DIR + iteration);
      classifier.writeToSeqFiles(clustersOut);
      FileSystem fs = FileSystem.get(outPath.toUri(), conf);
      iteration++;
      if (isConverged(clustersOut, conf, fs)) {
        break;
      }
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    FileSystem fs = FileSystem.get(pointsPath.toUri(), conf);
    List<VectorWritable> points = TestKmeansClustering.getPointsWritable(TestKmeansClustering.REFERENCE);
    ClusteringTestUtils.writePointsToFile(points, new Path(pointsPath, "file1"), fs, conf);
    Path path = new Path(priorPath, "priorClassifier");
    ClusterClassifier prior = newKlusterClassifier();
    prior.writeToSeqFiles(path);
    assertEquals(3, prior.getModels().size());
    System.out.println("Prior");
    for (Cluster cluster : prior.getModels()) {
      System.out.println(cluster.asFormatString(null));
    }
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    FileSystem fs = FileSystem.get(pointsPath.toUri(), conf);
    List<VectorWritable> points = TestKmeansClustering.getPointsWritable(TestKmeansClustering.REFERENCE);
    ClusteringTestUtils.writePointsToFile(points, new Path(pointsPath, "file1"), fs, conf);
    Path path = new Path(priorPath, "priorClassifier");
    ClusterClassifier prior = newKlusterClassifier();
    prior.writeToSeqFiles(path);
    ClusteringPolicy policy = new KMeansClusteringPolicy();
    ClusterClassifier.writePolicy(policy, path);
    assertEquals(3, prior.getModels().size());
    System.out.println("Prior");
    for (Cluster cluster : prior.getModels()) {
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    for (Vector point : points) {
      initialClusters.add(new SoftCluster(point, id++, measure));
    }
    ClusterClassifier prior = new ClusterClassifier(initialClusters, new FuzzyKMeansClusteringPolicy(m, threshold));
    Path priorPath = new Path(output, "classifier-0");
    prior.writeToSeqFiles(priorPath);
   
    ClusterIterator.iterateSeq(conf, samples, priorPath, output, maxIterations);
    loadClustersWritable(output);
  }
 
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    for (Model<VectorWritable> cluster : modelDist.sampleFromPrior(numClusters)) {
      models.add((Cluster) cluster);
    }
    ClusterClassifier prior = new ClusterClassifier(models, new DirichletClusteringPolicy(numClusters, alpha0));
    Path priorPath = new Path(output, Cluster.INITIAL_CLUSTERS_DIR);
    prior.writeToSeqFiles(priorPath);
    Configuration conf = new Configuration();
    ClusterIterator.iterateSeq(conf, input, priorPath, output, numIterations);
  }
 
  private static void runSequentialDirichletClusterer(Path input, Path output,
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    for (Vector point : points) {
      initialClusters.add(new org.apache.mahout.clustering.kmeans.Kluster(point, id++, measure));
    }
    ClusterClassifier prior = new ClusterClassifier(initialClusters, new KMeansClusteringPolicy(convergenceDelta));
    Path priorPath = new Path(output, Cluster.INITIAL_CLUSTERS_DIR);
    prior.writeToSeqFiles(priorPath);
   
    ClusterIterator.iterateSeq(conf, samples, priorPath, output, maxIterations);
    loadClustersWritable(output);
  }
 
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Examples of org.apache.mahout.clustering.classify.ClusterClassifier.writeToSeqFiles()

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    for (Vector point : points) {
      initialClusters.add(new org.apache.mahout.clustering.kmeans.Kluster(point, id++, measure));
    }
    ClusterClassifier prior = new ClusterClassifier(initialClusters, new KMeansClusteringPolicy(convergenceDelta));
    Path priorPath = new Path(output, Cluster.INITIAL_CLUSTERS_DIR);
    prior.writeToSeqFiles(priorPath);
   
    ClusterIterator.iterateSeq(conf, samples, priorPath, output, maxIterations);
    loadClustersWritable(output);
  }
 
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