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

    
    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

        }
        else {
          es = new RealBasicEventStream(new PlainTextByLineDataStream(datafr));
        }
        GIS.SMOOTHING_OBSERVATION = SMOOTHING_OBSERVATION;
        AbstractModel model;
        if (type.equals("maxent")) {
        
          if (!real) {
            model = GIS.trainModel(es,USE_SMOOTHING);
          }

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Examples of opennlp.model.AbstractModel


      File outputFile = new File(modelFileName);


      AbstractModelWriter writer;


      AbstractModel model;
      if (type.equals("maxent")) {
  GIS.SMOOTHING_OBSERVATION = SMOOTHING_OBSERVATION;


        if (!real) {
          model = GIS.trainModel(es, maxit, cutoff, sigma);

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Examples of opennlp.model.AbstractModel

    
    // build
    System.err.println("Training builder");
    opennlp.model.EventStream bes = new ParserEventStream(parseSamples, rules, ParserEventTypeEnum.BUILD, mdict);
    Map<String, String> buildReportMap = new HashMap<String, String>();
    AbstractModel buildModel = TrainUtil.train(bes, mlParams.getSettings("build"), buildReportMap);
    mergeReportIntoManifest(manifestInfoEntries, buildReportMap, "build");
    
    parseSamples.reset();
    
    // tag
    POSModel posModel = POSTaggerME.train(languageCode, new PosSampleStream(parseSamples), 
        mlParams.getParameters("tagger"), null, null);
    
    parseSamples.reset();
    
    // chunk
    ChunkerModel chunkModel = ChunkerME.train(languageCode, 
        new ChunkSampleStream(parseSamples),
        new ChunkContextGenerator(), mlParams.getParameters("chunker"));
    
    parseSamples.reset();
    
    // check
    System.err.println("Training checker");
    opennlp.model.EventStream kes = new ParserEventStream(parseSamples, rules, ParserEventTypeEnum.CHECK);
    Map<String, String> checkReportMap = new HashMap<String, String>();
    AbstractModel checkModel = TrainUtil.train(kes, mlParams.getSettings("check"), checkReportMap);
    mergeReportIntoManifest(manifestInfoEntries, checkReportMap, "check");


    // TODO: Remove cast for HeadRules
    return new ParserModel(languageCode, buildModel, checkModel,
        posModel, chunkModel, (opennlp.tools.parser.lang.en.HeadRules) rules,

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Examples of opennlp.model.AbstractModel

    // build
    System.err.println("Training builder");
    opennlp.model.EventStream bes = new ParserEventStream(parseSamples, rules,
        ParserEventTypeEnum.BUILD, mdict);
    Map<String, String> buildReportMap = new HashMap<String, String>();
    AbstractModel buildModel = TrainUtil.train(bes, mlParams.getSettings("build"), buildReportMap);
    opennlp.tools.parser.chunking.Parser.mergeReportIntoManifest(manifestInfoEntries, buildReportMap, "build");
    
    parseSamples.reset();
    
    // check
    System.err.println("Training checker");
    opennlp.model.EventStream kes = new ParserEventStream(parseSamples, rules,
        ParserEventTypeEnum.CHECK);
    Map<String, String> checkReportMap = new HashMap<String, String>();
    AbstractModel checkModel = TrainUtil.train(kes, mlParams.getSettings("check"), checkReportMap);
    opennlp.tools.parser.chunking.Parser.mergeReportIntoManifest(manifestInfoEntries, checkReportMap, "check");
    
    parseSamples.reset();
    
    // attach 
    System.err.println("Training attacher");
    opennlp.model.EventStream attachEvents = new ParserEventStream(parseSamples, rules,
        ParserEventTypeEnum.ATTACH);
    Map<String, String> attachReportMap = new HashMap<String, String>();
    AbstractModel attachModel = TrainUtil.train(attachEvents, mlParams.getSettings("attach"), attachReportMap);
    opennlp.tools.parser.chunking.Parser.mergeReportIntoManifest(manifestInfoEntries, attachReportMap, "attach");
    
    // TODO: Remove cast for HeadRules
    return new ParserModel(languageCode, buildModel, checkModel,
        attachModel, posModel, chunkModel,

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Examples of opennlp.model.AbstractModel

       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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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

  @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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Examples of opennlp.model.AbstractModel

      // 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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Examples of opennlp.model.AbstractModel


    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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