Examples of EigencutsAffinityCutsCombiner

org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> redWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      redContext = DummyRecordWriter.build(combiner, conf, redWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), redContext);
    }
    
    // test the number of cuts, there should be 2
    assertEquals("Number of cuts detected", 4, 
        redContext.getCounter(EigencutsAffinityCutsJob.CUTSCOUNTER.NUM_CUTS).getValue());

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Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> comWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      comContext = DummyRecordWriter.build(combiner, conf, comWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), comContext);
    }
    
    // finally, set up the reduction writers
    EigencutsAffinityCutsReducer reducer = new EigencutsAffinityCutsReducer();
    DummyRecordWriter<IntWritable, VectorWritable> redWriter = new

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Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> redWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      redContext = DummyRecordWriter.build(combiner, conf, redWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), redContext);
    }
    
    // test the number of cuts, there should be 2
    assertEquals("Number of cuts detected", 4, 
        redContext.getCounter(EigencutsAffinityCutsJob.CUTSCOUNTER.NUM_CUTS).getValue());

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Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> comWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      comContext = DummyRecordWriter.build(combiner, conf, comWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), comContext);
    }
    
    // finally, set up the reduction writers
    EigencutsAffinityCutsReducer reducer = new EigencutsAffinityCutsReducer();
    DummyRecordWriter<IntWritable, VectorWritable> redWriter = new

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Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> redWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      redContext = DummyRecordWriter.build(combiner, conf, redWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), redContext);
    }
    
    // test the number of cuts, there should be 2
    assertEquals("Number of cuts detected", 4, 
        redContext.getCounter(EigencutsAffinityCutsJob.CUTSCOUNTER.NUM_CUTS).getValue());

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Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> comWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      comContext = DummyRecordWriter.build(combiner, conf, comWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), comContext);
    }
    
    // finally, set up the reduction writers
    EigencutsAffinityCutsReducer reducer = new EigencutsAffinityCutsReducer();
    DummyRecordWriter<IntWritable, VectorWritable> redWriter = new

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Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> redWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      redContext = DummyRecordWriter.build(combiner, conf, redWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), redContext);
    }
    
    // test the number of cuts, there should be 2
    assertEquals("Number of cuts detected", 4, 
        redContext.getCounter(EigencutsAffinityCutsJob.CUTSCOUNTER.NUM_CUTS).getValue());

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Examples of org.apache.mahout.clustering.spectral.eigencuts.EigencutsAffinityCutsJob.EigencutsAffinityCutsCombiner

    // we can't use the mapper (since we have no way of manually setting
    // the Context.workingPath() )
    Map<Text, List<VertexWritable>> data = buildMapData(affinity, sensitivity, this.sensitivity);
     
    // now, set up the combiner
    EigencutsAffinityCutsCombiner combiner = new EigencutsAffinityCutsCombiner();
    DummyRecordWriter<Text, VertexWritable> comWriter =
      new DummyRecordWriter<Text, VertexWritable>();
    Reducer<Text, VertexWritable, Text, VertexWritable>.Context 
      comContext = DummyRecordWriter.build(combiner, conf, comWriter, Text.class,
      VertexWritable.class);
    
    // perform the combining
    for (Map.Entry<Text, List<VertexWritable>> entry : data.entrySet()) {
      combiner.reduce(entry.getKey(), entry.getValue(), comContext);
    }
    
    // finally, set up the reduction writers
    EigencutsAffinityCutsReducer reducer = new EigencutsAffinityCutsReducer();
    DummyRecordWriter<IntWritable, VectorWritable> redWriter = new

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