Examples of AbstractModel

com.caucho.naming.AbstractModel
Abstract data model behind Resin's JNDI.
com.clearnlp.classification.model.AbstractModel
Abstract model. @since 1.0.0 @author Jinho D. Choi ({@code jdchoi77@gmail.com})
edu.wpi.cs.wpisuitetng.modules.AbstractModel
Defines the behavior for permissions @author mpdelladonna
fr.yogourt.model.AbstractModel
opennlp.model.AbstractModel
opennlp.tools.ml.model.AbstractModel
org.openrdf.model.impl.AbstractModel

Examples of opennlp.model.AbstractModel


    String lang = args[1];
    String packageName = args[2];
    String modelName = args[3];


    AbstractModel chunkerModel = new GenericModelReader(
        new BinaryFileDataReader(new FileInputStream(modelName))).getModel();


    ChunkerModel packageModel = new ChunkerModel(lang, chunkerModel);
    packageModel.serialize(new FileOutputStream(packageName));
  }

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Examples of opennlp.model.AbstractModel

    
    POSContextGenerator contextGenerator = new DefaultPOSContextGenerator(ngramDictionary);
    
    Map<String, String> manifestInfoEntries = new HashMap<String, String>();
    
    AbstractModel posModel;
    
    if (!TrainUtil.isSequenceTraining(trainParams.getSettings())) {
      
      EventStream es = new POSSampleEventStream(samples, contextGenerator);

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Examples of opennlp.model.AbstractModel

    
    Map<String, String> manifestInfoEntries = new HashMap<String, String>();
    
    EventStream es = new ChunkerEventStream(in, contextGenerator);
    
    AbstractModel maxentModel = TrainUtil.train(es, mlParams.getSettings(), manifestInfoEntries);
    
    return new ChunkerModel(lang, maxentModel, manifestInfoEntries);
  }

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Examples of opennlp.model.AbstractModel

      // TODO: training individual models should be in the chunking parser, not here
      // Training build
      System.out.println("Training builder");
      opennlp.model.EventStream bes = new ParserEventStream(parseSamples, 
          originalModel.getHeadRules(), ParserEventTypeEnum.BUILD, mdict);
      AbstractModel buildModel = Parser.train(bes, 
          parameters.getIterations(), parameters.getCutoff());
      
      parseSamples.close();
      
      return originalModel.updateBuildModel(buildModel);

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Examples of opennlp.model.AbstractModel

   * @param modelFile
   * @throws IOException
   */
  @Deprecated
  public static void trainMaxentModel(EventStream evc, File modelFile) throws IOException {
    AbstractModel model = trainMaxentModel(evc, 100,5);
    new SuffixSensitiveGISModelWriter(model, modelFile).persist();
  }

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Examples of opennlp.model.AbstractModel

      int iterations = 100;
      if (args.length > ai) {
        cutoff = Integer.parseInt(args[ai++]);
        iterations = Integer.parseInt(args[ai++]);
      }
      AbstractModel mod;
      if (dict != null) {
        buildDictionary(dict, inFile, cutoff);
      }
      if (sequence) {
        POSSampleSequenceStream ss;

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Examples of opennlp.model.AbstractModel

    }
    ParserEventTypeEnum etype = null;
    boolean fun = false;
    int ai = 0;
    Dictionary dict = null;
    AbstractModel model = null;


    while (ai < args.length && args[ai].startsWith("-")) {
      if (args[ai].equals("-build")) {
        etype = ParserEventTypeEnum.BUILD;
      }
      else if (args[ai].equals("-attach")) {
        etype = ParserEventTypeEnum.ATTACH;
      }
      else if (args[ai].equals("-chunk")) {
        etype = ParserEventTypeEnum.CHUNK;
      }
      else if (args[ai].equals("-check")) {
        etype = ParserEventTypeEnum.CHECK;
      }
      else if (args[ai].equals("-tag")) {
        etype = ParserEventTypeEnum.TAG;
      }
      else if (args[ai].equals("-fun")) {
        fun = true;
      }
      else if (args[ai].equals("-dict")) {
        ai++;
        dict = new Dictionary(new FileInputStream(args[ai]));
      }
      else if (args[ai].equals("-model")) {
        ai++;
        model = (new SuffixSensitiveGISModelReader(new File(args[ai]))).getModel();
      }
      else {
        System.err.println("Invalid option " + args[ai]);
        System.exit(1);
      }
      ai++;
    }
    HeadRules rules = new opennlp.tools.parser.lang.en.HeadRules(args[ai++]);
    if (fun) {
      Parse.useFunctionTags(true);
    }
    opennlp.model.EventStream es = new ParserEventStream(new ParseSampleStream(new PlainTextByLineStream(new java.io.InputStreamReader(System.in))), rules, etype, dict);
    while (es.hasNext()) {
      Event e = es.next();
      if (model != null) {
        System.out.print(model.eval(e.getContext())[model.getIndex(e.getOutcome())]+" ");
      }
      System.out.println(e);
    }
  }

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Examples of opennlp.model.AbstractModel

          Collections.addAll(dictTags, posDict.getTags(word)); 
        }
        
        Set<String> modelTags = new HashSet<String>();
        
        AbstractModel posModel = getPosModel();
        
        for  (int i = 0; i < posModel.getNumOutcomes(); i++) {
          modelTags.add(posModel.getOutcome(i));
        }
        
        if (!modelTags.containsAll(dictTags)) {
          throw new InvalidFormatException("Tag dictioinary contains tags " +
              "which are unkown by the model!");

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Examples of opennlp.model.AbstractModel


    String lang = args[1];
    String packageName = args[2];
    String modelName = args[3];


    AbstractModel chunkerModel = new GenericModelReader(
        new BinaryFileDataReader(new FileInputStream(modelName))).getModel();


    ChunkerModel packageModel = new ChunkerModel(lang, chunkerModel);
    packageModel.serialize(new FileOutputStream(packageName));
  }

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Examples of opennlp.model.AbstractModel


    Map<String, String> manifestInfoEntries = new HashMap<String, String>();


    EventStream es = new ChunkerEventStream(in, factory.getContextGenerator());


    AbstractModel maxentModel = TrainUtil.train(es, mlParams.getSettings(),
        manifestInfoEntries);


    return new ChunkerModel(lang, maxentModel, manifestInfoEntries, factory);
  }

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