Package opennlp.model

Examples of opennlp.model.AbstractModel

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       featureGenerators = new FeatureGenerator[]{defaultFeatureGenerator};
     }
    
     Map<String, String> manifestInfoEntries = new HashMap<String, String>();
    
     AbstractModel model = TrainUtil.train(
         new DocumentCategorizerEventStream(samples, featureGenerators),
         mlParams.getSettings(), manifestInfoEntries);
      
     return new DoccatModel(languageCode, model, manifestInfoEntries);
   }
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      // 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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  @Override
  protected void validateArtifactMap() throws InvalidFormatException {
    super.validateArtifactMap();
   
    if (artifactMap.get(MAXENT_MODEL_ENTRY_NAME) instanceof AbstractModel) {
      AbstractModel model = (AbstractModel) artifactMap.get(MAXENT_MODEL_ENTRY_NAME);
      isModelValid(model);
    }
    else {
      throw new InvalidFormatException("Token Name Finder model is incomplete!");
    }
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      // TODO: Maybe that should be part of the ChunkingParser ...
      // Training build
      System.out.println("Training check model");
      opennlp.model.EventStream bes = new ParserEventStream(parseSamples,
          originalModel.getHeadRules(), ParserEventTypeEnum.CHECK, mdict);
      AbstractModel checkModel = Parser.train(bes,
          parameters.getIterations(), parameters.getCutoff());
     
      parseSamples.close();
     
      return originalModel.updateCheckModel(checkModel);
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    String languageCode = args[ai++];
    String packageName = args[ai++];
    String modelName = args[ai];

    AbstractModel model = new BinaryGISModelReader(new DataInputStream(
        new FileInputStream(modelName))).getModel();

    TokenizerModel packageModel = new TokenizerModel(languageCode, model,
        alphaNumericOptimization);
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        .getArtifact(TAG_DICTIONARY_ENTRY_NAME);

    if (tagdictEntry != null) {
      if (tagdictEntry instanceof POSDictionary) {
        if(!this.artifactProvider.isLoadedFromSerialized()) {
          AbstractModel posModel = this.artifactProvider
              .getArtifact(POSModel.POS_MODEL_ENTRY_NAME);
          POSDictionary posDict = (POSDictionary) tagdictEntry;
          validatePOSDictionary(posDict, posModel);
        }
      } else {
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    POSContextGenerator contextGenerator = posFactory.getPOSContextGenerator();
   
    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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    EventStream eventStream = new TokSpanEventStream(samples,
        factory.isUseAlphaNumericOptmization(),
        factory.getAlphaNumericPattern(), factory.getContextGenerator());

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

    return new TokenizerModel(maxentModel, manifestInfoEntries,
        factory);
  }
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    EventStream eventStream = new TokSpanEventStream(samples,
        useAlphaNumericOptimization, factory.getAlphanumeric(languageCode),
        factory.createTokenContextGenerator(languageCode,
            getAbbreviations(abbreviations)));

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

    return new TokenizerModel(languageCode, maxentModel, abbreviations,
        useAlphaNumericOptimization, manifestInfoEntries);
  }
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   * @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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Related Classes of opennlp.model.AbstractModel

  • CreateModel
  • opennlp.maxent.GISModel
  • opennlp.maxent.io.SuffixSensitiveGISModelReader
  • opennlp.maxent.MaxentPrepAttachTest
  • opennlp.maxent.ModelTrainer
  • opennlp.maxent.quasinewton.QNTrainerTest
  • opennlp.perceptron.PerceptronModel
  • opennlp.perceptron.PerceptronPrepAttachTest
  • opennlp.tools.chunker.ChunkerME
  • opennlp.tools.chunker.ChunkerModel
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