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

  @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


    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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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


    String languageCode = args[ai++];
    String packageName = args[ai++];
    String modelName = args[ai];


    AbstractModel model = new GenericModelReader(new File(modelName)).getModel();
    SentenceModel packageModel = new SentenceModel(languageCode, model, useTokenEnd, abbreviations);
    packageModel.serialize(new FileOutputStream(packageName));
  }

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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

    // TODO: Fix the EventStream to throw exceptions when training goes wrong
    EventStream eventStream = new SDEventStream(samples,
        factory.createSentenceContextGenerator(languageCode, getAbbreviations(abbreviations)),
        factory.createEndOfSentenceScanner(languageCode));
    
    AbstractModel sentModel = TrainUtil.train(eventStream, mlParams.getSettings(), manifestInfoEntries);
    
    return new SentenceModel(languageCode, sentModel,
        useTokenEnd, abbreviations, manifestInfoEntries);
  }

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Examples of opennlp.model.AbstractModel

 */
public class PerceptronPrepAttachTest {


  @Test
  public void testPerceptronOnPrepAttachData() throws IOException {
    AbstractModel model = 
        new PerceptronTrainer().trainModel(400, 
        new TwoPassDataIndexer(createTrainingStream(), 1, false), 1);


    testModel(model, 0.7650408516959644);
  }

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Examples of opennlp.model.AbstractModel

    Map<String, String> trainParams = new HashMap<String, String>();
    trainParams.put(TrainUtil.ALGORITHM_PARAM, TrainUtil.PERCEPTRON_VALUE);
    trainParams.put(TrainUtil.CUTOFF_PARAM, Integer.toString(1));
    trainParams.put("UseSkippedAveraging", Boolean.toString(true));
    
    AbstractModel model = TrainUtil.train(createTrainingStream(), trainParams, null);
    
    testModel(model, 0.773706362961129);
  }

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Examples of opennlp.model.AbstractModel

    trainParams.put(TrainUtil.ALGORITHM_PARAM, TrainUtil.PERCEPTRON_VALUE);
    trainParams.put(TrainUtil.CUTOFF_PARAM, Integer.toString(1));
    trainParams.put(TrainUtil.ITERATIONS_PARAM, Integer.toString(500));
    trainParams.put("Tolerance", Double.toString(0.0001d));
    
    AbstractModel model = TrainUtil.train(createTrainingStream(), trainParams, null);
    
    testModel(model, 0.7677642980935875);
  }

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Examples of opennlp.model.AbstractModel

    trainParams.put(TrainUtil.ALGORITHM_PARAM, TrainUtil.PERCEPTRON_VALUE);
    trainParams.put(TrainUtil.CUTOFF_PARAM, Integer.toString(1));
    trainParams.put(TrainUtil.ITERATIONS_PARAM, Integer.toString(500));
    trainParams.put("StepSizeDecrease", Double.toString(0.06d));
    
    AbstractModel model = TrainUtil.train(createTrainingStream(), trainParams, null);
    
    testModel(model, 0.7756870512503095);
  }

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