Package org.apache.mahout.utils.clustering

Examples of org.apache.mahout.utils.clustering.ClusterDumper$TermIndexWeight

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                                    convergenceDelta,
                                    maxIterations,
                                    true,
                                    true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper =
        new ClusterDumper(new Path(output, "clusters-" + maxIterations), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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                          true,
                          true,
                          0.0,
                          false);
    // run ClusterDumper
    ClusterDumper clusterDumper =
        new ClusterDumper(finalClusterPath(conf, output, maxIterations), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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                        true,
                        emitMostLikely,
                        threshold,
                        false);
    // run ClusterDumper
    ClusterDumper clusterDumper =
        new ClusterDumper(new Path(output, "clusters-" + maxIterations), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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    InputDriver.runJob(input, directoryContainingConvertedInput,
        "org.apache.mahout.math.RandomAccessSparseVector");
    CanopyDriver.run(new Configuration(), directoryContainingConvertedInput,
        output, measure, t1, t2, true, 0.0, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(new Path(output,
        "clusters-0-final"), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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    Path directoryContainingConvertedInput = new Path(output, DIRECTORY_CONTAINING_CONVERTED_INPUT);
    InputDriver.runJob(input, directoryContainingConvertedInput, "org.apache.mahout.math.RandomAccessSparseVector");
    DirichletDriver.run(new Configuration(), directoryContainingConvertedInput, output, description, numModels,
        maxIterations, alpha0, true, emitMostLikely, threshold, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(new Path(output, "clusters-*-final"), new Path(output,
        "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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    InputDriver.runJob(input, directoryContainingConvertedInput);
    MeanShiftCanopyDriver.run(conf, directoryContainingConvertedInput, output,
        measure, kernelProfile, t1, t2, convergenceDelta, maxIterations, true,
        true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(new Path(output,
        "clusters-*-final"), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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    // run ClusterDumper
    Path outGlob = new Path(output, "clusters-*-final");
    Path clusteredPoints = new Path(output,
            "clusteredPoints");
    log.info("Dumping out clusters from clusters: {} and clusteredPoints: {}", outGlob, clusteredPoints);
    ClusterDumper clusterDumper = new ClusterDumper(outGlob, clusteredPoints);
    clusterDumper.printClusters(null);
  }
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        false);
    log.info("Running KMeans");
    KMeansDriver.run(conf, directoryContainingConvertedInput, new Path(canopyOutput, Cluster.INITIAL_CLUSTERS_DIR
        + "-final"), output, measure, convergenceDelta, maxIterations, true, 0.0, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(new Path(output, "clusters-*-final"), new Path(output,
        "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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        .run(new Configuration(), directoryContainingConvertedInput, canopyOutput, measure, t1, t2, false, 0.0, false);
    log.info("Running FuzzyKMeans");
    FuzzyKMeansDriver.run(directoryContainingConvertedInput, new Path(canopyOutput, "clusters-0-final"), output,
        measure, convergenceDelta, maxIterations, fuzziness, true, true, 0.0, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(new Path(output, "clusters-*-final"), new Path(output,
        "clusteredPoints"));
    clusterDumper.printClusters(null);
  }
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                       int maxLabels) {
    this.indexDir = indexDir;
    this.contentField = contentField;
    this.minNumIds = minNumIds;
    this.maxLabels = maxLabels;
    ClusterDumper clusterDumper = new ClusterDumper(seqFileDir, pointsDir);
    this.clusterIdToPoints = clusterDumper.getClusterIdToPoints();
  }
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