Example usage for opennlp.tools.util TrainingParameters put

List of usage examples for opennlp.tools.util TrainingParameters put

Introduction

In this page you can find the example usage for opennlp.tools.util TrainingParameters put.

Prototype

public void put(String key, boolean value) 

Source Link

Usage

From source file:io.learningbox.controller.APIController.java

@RequestMapping(value = "/categorize/{area}", method = RequestMethod.POST)
public SortedMap<Double, Set<String>> categorize(@PathVariable final String area, @RequestBody String input)
        throws IOException {
    List<LearningSet> l = repository.findByArea(area);
    final Iterator<LearningSet> sets = l.iterator();

    ObjectStream<DocumentSample> stream = new ObjectStream<DocumentSample>() {

        @Override/*from  w  w w . ja va 2 s  . c  o m*/
        public DocumentSample read() throws IOException {
            if (sets.hasNext()) {
                LearningSet s = sets.next();

                return new DocumentSample(s.getCategory(), s.getText());
            }
            return null;
        }

        @Override
        public void reset() throws IOException, UnsupportedOperationException {
            throw new UnsupportedOperationException();
        }

        @Override
        public void close() throws IOException {
            //Do nothing
        }
    };

    TrainingParameters trainingParameters = TrainingParameters.defaultParams();
    trainingParameters.put(TrainingParameters.ITERATIONS_PARAM, Integer.toString(1000));
    trainingParameters.put(TrainingParameters.CUTOFF_PARAM, Integer.toString(1));

    DoccatModel model = DocumentCategorizerME.train("en", stream, trainingParameters, new DoccatFactory());
    DocumentCategorizerME myCategorizer = new DocumentCategorizerME(model);
    return myCategorizer.sortedScoreMap(input);
}

From source file:de.tudarmstadt.ukp.dkpro.core.opennlp.OpenNlpNamedEntityRecognizerTrainer.java

@Override
public void initialize(UimaContext aContext) throws ResourceInitializationException {
    super.initialize(aContext);

    stream = new CasNameSampleStream();

    TrainingParameters params = new TrainingParameters();
    params.put(TrainingParameters.ALGORITHM_PARAM, algorithm);
    //        params.put(TrainingParameters.TRAINER_TYPE_PARAM,
    //                TrainerFactory.getTrainerType(params.getSettings()).name());
    params.put(TrainingParameters.ITERATIONS_PARAM, Integer.toString(iterations));
    params.put(TrainingParameters.CUTOFF_PARAM, Integer.toString(cutoff));
    params.put(BeamSearch.BEAM_SIZE_PARAMETER, Integer.toString(beamSize));

    byte featureGenCfg[] = loadFeatureGen(featureGen);

    Callable<TokenNameFinderModel> trainTask = () -> {
        try {/*from w  ww . j a  va 2 s  .co  m*/
            return NameFinderME.train(language, null, stream, params, new TokenNameFinderFactory(featureGenCfg,
                    Collections.<String, Object>emptyMap(), sequenceEncoding.getCodec()));
        } catch (Throwable e) {
            stream.close();
            throw e;
        }
    };

    future = executor.submit(trainTask);
}