Package org.apache.mahout.classifier.bayes.mapreduce.common

Examples of org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureReducer


  
    mapper.map(new Text("baz"), new Text("red giant"), mapperOutput, Reporter.NULL);
    mapper.map(new Text("baz"), new Text("white dwarf"), mapperOutput, Reporter.NULL);
    mapper.map(new Text("baz"), new Text("cool black hole"), mapperOutput, Reporter.NULL);
   
    BayesFeatureReducer reducer = new BayesFeatureReducer();
    reducer.configure(conf);
   
    DummyOutputCollector<StringTuple,DoubleWritable> reducerOutput = new DummyOutputCollector<StringTuple,DoubleWritable>();
    Map<StringTuple, List<DoubleWritable>> outputData = mapperOutput.getData();
   
    // put the mapper output in the expected order (emulate shuffle)
    FeatureLabelComparator cmp = new FeatureLabelComparator();
    Collection<StringTuple> keySet = new TreeSet<StringTuple>(cmp);
    keySet.addAll(mapperOutput.getKeys());
   
    for (StringTuple k: keySet) {
      List<DoubleWritable> v = outputData.get(k);
      reducer.reduce(k, v.iterator(), reducerOutput, Reporter.NULL);
    }

    return reducerOutput;
  }
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    mapper.map(new Text("baz"), new Text("red giant"), mapperOutput, Reporter.NULL);
    mapper.map(new Text("baz"), new Text("white dwarf"), mapperOutput, Reporter.NULL);
    mapper.map(new Text("baz"), new Text("cool black hole"), mapperOutput, Reporter.NULL);
   
    BayesFeatureReducer reducer = new BayesFeatureReducer();
    reducer.configure(conf);
   
    DummyOutputCollector<StringTuple,DoubleWritable> reducerOutput = new DummyOutputCollector<StringTuple,DoubleWritable>();
    Map<StringTuple, List<DoubleWritable>> outputData = mapperOutput.getData();
   
    // put the mapper output in the expected order (emulate shuffle)
    FeatureLabelComparator cmp = new FeatureLabelComparator();
    Collection<StringTuple> keySet = new TreeSet<StringTuple>(cmp);
    keySet.addAll(mapperOutput.getKeys());
   
    for (StringTuple k: keySet) {
      List<DoubleWritable> v = outputData.get(k);
      reducer.reduce(k, v.iterator(), reducerOutput, Reporter.NULL);
    }

    return reducerOutput;
  }
View Full Code Here

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