Package org.apache.mahout.common

Examples of org.apache.mahout.common.Parameters

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import org.apache.commons.codec.language.DoubleMetaphone;
import org.apache.mahout.common.Parameters;

public class CreateTwitterUserDataset {
  public static void main(String args[]) throws Exception {
    Parameters params = new Parameters();
    params.set("splitPattern", "\t");
    String inputDir = "tweets.txt";
    String outputDir = "twitter_seqfiles";
    params.set("input", inputDir);
    params.set("output", outputDir);
    params.set("selectedField", "1"); // tweet
    params.set("groupByField", "0"); // username
    ByKeyGroupingJob.startJob(params);
    DoubleMetaphone filter = new DoubleMetaphone();
// TODO: change these terms?!
    System.out.println(filter.encode("Loke"));
    System.out.println(filter.encode("companymancomic"));
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  }
 
  @Override
  protected void setup(Context context) throws IOException, InterruptedException {
    super.setup(context);
    Parameters params = Parameters.fromString(context.getConfiguration().get("pfp.parameters", ""));
   
    int i = 0;
    for (Pair<String,Long> e : PFPGrowth.deserializeList(params, "fList", context.getConfiguration())) {
      fMap.put(e.getFirst(), i++);
    }
   
    splitter = Pattern.compile(params.get("splitPattern", PFPGrowth.SPLITTER.toString()));
   
  }
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  }
 
  @Override
  protected void setup(Context context) throws IOException, InterruptedException {
    super.setup(context);
    Parameters params = Parameters.fromString(context.getConfiguration().get("pfp.parameters", ""));
    splitter = Pattern.compile(params.get("splitPattern", PFPGrowth.SPLITTER.toString()));
  }
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  @Override
  protected void setup(Context context) throws IOException, InterruptedException {
   
    super.setup(context);
    Parameters params = Parameters.fromString(context.getConfiguration().get("pfp.parameters", ""));
   
    int i = 0;
    for (Pair<String,Long> e : PFPGrowth.deserializeList(params, "fList", context.getConfiguration())) {
      featureReverseMap.add(e.getFirst());
      fMap.put(e.getFirst(), i++);
     
    }
   
    Map<String,Long> gList = PFPGrowth.deserializeMap(params, "gList", context.getConfiguration());
   
    for (Entry<String,Long> entry : gList.entrySet()) {
      IntArrayList groupList = groupFeatures.get(entry.getValue());
      Integer itemInteger = fMap.get(entry.getKey());
      if (groupList != null) {
        groupList.add(itemInteger);
      } else {
        groupList = new IntArrayList();
        groupList.add(itemInteger);
        groupFeatures.put(entry.getValue(), groupList);
      }
     
    }
    maxHeapSize = Integer.valueOf(params.get("maxHeapSize", "50"));
    minSupport = Integer.valueOf(params.get("minSupport", "3"));
    FPTreeDepthCache.setFirstLevelCacheSize(Integer.valueOf(params.get("treeCacheSize", Integer
        .toString(FPTreeDepthCache.getFirstLevelCacheSize()))));
  }
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  }
 
  @Override
  protected void setup(Context context) throws IOException, InterruptedException {
    super.setup(context);
    Parameters params = Parameters.fromString(context.getConfiguration().get("pfp.parameters", ""));
   
    OpenObjectIntHashMap<String> fMap = new OpenObjectIntHashMap<String>();
    int i = 0;
    for (Pair<String,Long> e : PFPGrowth.deserializeList(params, "fList", context.getConfiguration())) {
      fMap.put(e.getFirst(), i++);
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      if (cmdLine.hasOption(helpOpt)) {
        CommandLineUtil.printHelp(group);
        return;
      }
     
      Parameters params = new Parameters();
     
      if (cmdLine.hasOption(minSupportOpt)) {
        String minSupportString = (String) cmdLine.getValue(minSupportOpt);
        params.set("minSupport", minSupportString);
      }
      if (cmdLine.hasOption(maxHeapSizeOpt)) {
        String maxHeapSizeString = (String) cmdLine.getValue(maxHeapSizeOpt);
        params.set("maxHeapSize", maxHeapSizeString);
      }
      if (cmdLine.hasOption(numGroupsOpt)) {
        String numGroupsString = (String) cmdLine.getValue(numGroupsOpt);
        params.set("numGroups", numGroupsString);
      }
     
      if (cmdLine.hasOption(treeCacheOpt)) {
        String numTreeCacheString = (String) cmdLine.getValue(treeCacheOpt);
        params.set("treeCacheSize", numTreeCacheString);
      }
     
      if (cmdLine.hasOption(recordSplitterOpt)) {
        String patternString = (String) cmdLine.getValue(recordSplitterOpt);
        params.set("splitPattern", patternString);
      }
     
      String encoding = "UTF-8";
      if (cmdLine.hasOption(encodingOpt)) {
        encoding = (String) cmdLine.getValue(encodingOpt);
      }
      params.set("encoding", encoding);
      String inputDir = (String) cmdLine.getValue(inputDirOpt);
      String outputDir = (String) cmdLine.getValue(outputOpt);
     
      params.set("input", inputDir);
      params.set("output", outputDir);
     
      String classificationMethod = (String) cmdLine.getValue(methodOpt);
      if (classificationMethod.equalsIgnoreCase("sequential")) {
        runFPGrowth(params);
      } else if (classificationMethod.equalsIgnoreCase("mapreduce")) {
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  }
 
  @Override
  public void configure(JobConf job) {
    try {
      Parameters params = Parameters.fromString(job.get("bayes.parameters", ""));
      if (params.get("dataSource").equals("hbase")) {
        useHbase = true;
      } else {
        return;
      }
     
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      String vocabCountString = stringifier.toString(vocabCount);
      vocabCountString = job.get("cnaivebayes.vocabCount", vocabCountString);
      vocabCount = stringifier.fromString(vocabCountString);
     
      Parameters params = Parameters.fromString(job.get("bayes.parameters", ""));
      alphaI = Double.valueOf(params.get("alpha_i", "1.0"));
     
    } catch (IOException ex) {
      log.warn(ex.toString(), ex);
    }
  }
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  }
 
  @Override
  public void configure(JobConf job) {
    try {
      Parameters params = Parameters.fromString(job.get("bayes.parameters", ""));
      if (params.get("dataSource").equals("hbase")) {
        useHbase = true;
      } else {
        return;
      }
     
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  @Override
  public void configure(JobConf job) {
    try {
      log.info("Bayes Parameter {}", job.get("bayes.parameters"));
      Parameters params = Parameters.fromString(job.get("bayes.parameters", ""));
      gramSize = Integer.valueOf(params.get("gramSize"));
     
    } catch (IOException ex) {
      log.warn(ex.toString(), ex);
    }
  }
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Related Classes of org.apache.mahout.common.Parameters

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  • org.apache.hadoop.conf.Configuration
  • org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierMapper
  • org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerMapper
  • org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesThetaNormalizerReducer
  • org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerMapper
  • org.apache.mahout.classifier.bayes.mapreduce.cbayes.CBayesThetaNormalizerReducer
  • org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureMapper
  • org.apache.mahout.classifier.bayes.mapreduce.common.BayesFeatureReducer
  • org.apache.mahout.classifier.bayes.mapreduce.common.BayesTfIdfReducer
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