Examples of opennlp.tools.util.featuregen.WindowFeatureGenerator

opennlp.tools.util.featuregen.WindowFeatureGenerator
Generates previous and next features for a given {@link AdaptiveFeatureGenerator}. The window size can be specified. Features: Current token is always included unchanged Previous tokens are prefixed with p distance Next tokens are prefix with n distance

      contextGenerator = new DefaultNameContextGenerator(featureGenerator);
    }


    // NOTE: This didn't turn out to work well ... anybody using this actually ?!
    contextGenerator.addFeatureGenerator(
            new WindowFeatureGenerator(additionalContextFeatureGenerator, 8, 8));


    if (this.sequenceValidator == null) {
      this.sequenceValidator = new NameFinderSequenceValidator();
    }
  }

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  }


  static AdaptiveFeatureGenerator createFeatureGenerator() {
    return new CachedFeatureGenerator(
            new AdaptiveFeatureGenerator[]{
              new WindowFeatureGenerator(new TokenFeatureGenerator(), 2, 2),
              new WindowFeatureGenerator(new TokenClassFeatureGenerator(true), 2, 2),
              new OutcomePriorFeatureGenerator(),
              new PreviousMapFeatureGenerator(),
              new BigramNameFeatureGenerator(),
              new SentenceFeatureGenerator(true, false)
            });

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    if (codec == null) {
      this.codec = new BioCodec();
    }


    this.contextGenerator = contextGenerator;
    this.contextGenerator.addFeatureGenerator(new WindowFeatureGenerator(additionalContextFeatureGenerator, 8, 8));


    if (type != null)
      this.type = type;
    else
      this.type = "default";

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      contextGenerator = new DefaultNameContextGenerator(generator);
    else
      contextGenerator = new DefaultNameContextGenerator(createFeatureGenerator());
    
    contextGenerator.addFeatureGenerator(
          new WindowFeatureGenerator(additionalContextFeatureGenerator, 8, 8));
    
    beam = new BeamSearch<String>(beamSize, contextGenerator, this.model,
        new NameFinderSequenceValidator(), beamSize);
  }

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  @Deprecated
  public NameFinderME(MaxentModel mod, NameContextGenerator cg, int beamSize) {
    model = mod;
    contextGenerator = cg;


    contextGenerator.addFeatureGenerator(new WindowFeatureGenerator(additionalContextFeatureGenerator, 8, 8));
    beam = new BeamSearch<String>(beamSize, cg, mod,
        new NameFinderSequenceValidator(), beamSize);
  }

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  }


  private static AdaptiveFeatureGenerator createFeatureGenerator() {
   return new CachedFeatureGenerator(
         new AdaptiveFeatureGenerator[]{
           new WindowFeatureGenerator(new TokenFeatureGenerator(), 2, 2),
           new WindowFeatureGenerator(new TokenClassFeatureGenerator(true), 2, 2),
           new OutcomePriorFeatureGenerator(),
           new PreviousMapFeatureGenerator(),
           new BigramNameFeatureGenerator(),
           new SentenceFeatureGenerator(true, false)
           });

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   * @param contextGenerator The context generator used to generate features for the event stream.
   */
  public NameFinderEventStream(ObjectStream<NameSample> dataStream, String type, NameContextGenerator contextGenerator) {
    this.nameSampleStream = dataStream;
    this.contextGenerator = contextGenerator;
    this.contextGenerator.addFeatureGenerator(new WindowFeatureGenerator(additionalContextFeatureGenerator, 8, 8));
    
    if (type != null)
      this.type = type;
    else
      this.type = "default";

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Related Classes of opennlp.tools.util.featuregen.WindowFeatureGenerator

com.tamingtext.opennlp.NameFinderTest

opennlp.tools.namefind.NameFinderEventStream

opennlp.tools.namefind.NameFinderME

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