Package org.apache.mahout.common

Examples of org.apache.mahout.common.StringTuple

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                                                                   PathType.GLOB,
                                                                   null,
                                                                   null,
                                                                   true,
                                                                   conf)) {
      StringTuple key = record.getFirst();
      DoubleWritable value = record.getSecond();
      // Sum of weights in a Label
      if (key.stringAt(0).equals(BayesConstants.LABEL_THETA_NORMALIZER)) {
        datastore.setThetaNormalizer(key.stringAt(1), value.get());
        if (++count % 50000 == 0) {
          log.info("Read {} theta norms", count);
        }
      }
    }
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                                                                   PathType.GLOB,
                                                                   null,
                                                                   null,
                                                                   true,
                                                                   conf)) {
      StringTuple key = record.getFirst();
      DoubleWritable value = record.getSecond();
      if (key.stringAt(0).equals(BayesConstants.TOTAL_SUM)) {
        // Sum of weights for all Features and all Labels
        datastore.setSigmaJSigmaK(value.get());
        log.info("{}", value.get());
      }
    }
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                                                                   PathType.GLOB,
                                                                   null,
                                                                   null,
                                                                   true,
                                                                   conf)) {
      StringTuple key = record.getFirst();
      DoubleWritable value = record.getSecond();
      if (key.stringAt(0).equals(BayesConstants.LABEL_SUM)) {
        // Sum of counts of labels
        labelSum.put(key.stringAt(1), value.get());
      }
    }
    return labelSum;
  }
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                                                                   PathType.GLOB,
                                                                   null,
                                                                   null,
                                                                   true,
                                                                   conf)) {
      StringTuple key = record.getFirst();
      DoubleWritable value = record.getSecond();
      // Count of Documents in a Label
      if (key.stringAt(0).equals(BayesConstants.LABEL_COUNT)) {
        labelDocumentCounts.put(key.stringAt(1), value.get());
      }
    }
    return labelDocumentCounts;
  }
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                                                                   PathType.GLOB,
                                                                   null,
                                                                   null,
                                                                   true,
                                                                   conf)) {
      StringTuple key = record.getFirst();
      DoubleWritable value = record.getSecond();
      if (weightSum.size() > 1) {
        throw new IllegalStateException("Incorrect Sum File");
      } else if (key.stringAt(0).equals(BayesConstants.TOTAL_SUM)) {
        weightSum.put(BayesConstants.TOTAL_SUM, value.get());
      }
    }
    return weightSum.get(BayesConstants.TOTAL_SUM);
  }
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                                                                   true,
                                                                   conf)) {
      if (weightSum.size() > 1) {
        throw new IllegalStateException("Incorrect vocabCount File");
      }
      StringTuple key = record.getFirst();
      DoubleWritable value = record.getSecond();
      if (key.stringAt(0).equals(BayesConstants.FEATURE_SET_SIZE)) {
        weightSum.put(BayesConstants.FEATURE_SET_SIZE, value.get());
      }
    }
    return weightSum.get(BayesConstants.FEATURE_SET_SIZE);
  }
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    String label = key.stringAt(1);
   
    reporter.setStatus("Bayes Theta Normalizer Mapper: " + label);
   
    double weight = Math.log((value.get() + alphaI) / (labelWeightSum.get(label) + vocabCount));
    StringTuple thetaNormalizerTuple = new StringTuple(BayesConstants.LABEL_THETA_NORMALIZER);
    thetaNormalizerTuple.add(label);
    output.collect(thetaNormalizerTuple, new DoubleWritable(weight));
  }
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                                                                   PathType.GLOB,
                                                                   null,
                                                                   null,
                                                                   true,
                                                                   conf)) {
      StringTuple key = record.getFirst();
      DoubleWritable value = record.getSecond();
      String correctLabel = key.stringAt(1);
      String classifiedLabel = key.stringAt(2);
      Map<String,Integer> rowMatrix = confusionMatrix.get(correctLabel);
      if (rowMatrix == null) {
        rowMatrix = Maps.newHashMap();
      }
      Integer count = Double.valueOf(value.get()).intValue();
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        defaultCategory);
     
      String correctLabel = key.toString();
      String classifiedLabel = result.getLabel();
     
      StringTuple outputTuple = new StringTuple(BayesConstants.CLASSIFIER_TUPLE);
      outputTuple.add(correctLabel);
      outputTuple.add(classifiedLabel);
     
      output.collect(outputTuple, ONE);
    } catch (InvalidDatastoreException e) {
      throw new IOException(e);
    }
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    String label = key.stringAt(1);
   
    reporter.setStatus("Bayes Theta Normalizer Mapper: " + label);
   
    double weight = Math.log((value.get() + alphaI) / (labelWeightSum.get(label) + vocabCount));
    StringTuple thetaNormalizerTuple = new StringTuple(BayesConstants.LABEL_THETA_NORMALIZER);
    thetaNormalizerTuple.add(label);
    output.collect(thetaNormalizerTuple, new DoubleWritable(weight));
  }
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Related Classes of org.apache.mahout.common.StringTuple

  • com.digitalpebble.behemoth.mahout.BehemothTokenizerMapper
  • com.digitalpebble.behemoth.mahout.LuceneTokenizerMapper
  • org.apache.hadoop.io.Text
  • org.apache.mahout.classifier.bayes.io.SequenceFileModelReader
  • org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierDriver
  • org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierMapper
  • org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerMapper
  • org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerMapper
  • org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureMapper
  • org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureOutputFormat
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