Package opennlp.tools.ml.model

Examples of opennlp.tools.ml.model.AbstractModel

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    }
    ParserEventTypeEnum etype = null;
    boolean fun = false;
    int ai = 0;
    Dictionary dict = null;
    AbstractModel model = null;

    while (ai < args.length && args[ai].startsWith("-")) {
      if (args[ai].equals("-build")) {
        etype = ParserEventTypeEnum.BUILD;
      }
      else if (args[ai].equals("-attach")) {
        etype = ParserEventTypeEnum.ATTACH;
      }
      else if (args[ai].equals("-chunk")) {
        etype = ParserEventTypeEnum.CHUNK;
      }
      else if (args[ai].equals("-check")) {
        etype = ParserEventTypeEnum.CHECK;
      }
      else if (args[ai].equals("-tag")) {
        etype = ParserEventTypeEnum.TAG;
      }
      else if (args[ai].equals("-fun")) {
        fun = true;
      }
      else if (args[ai].equals("-dict")) {
        ai++;
        dict = new Dictionary(new FileInputStream(args[ai]));
      }
      else if (args[ai].equals("-model")) {
        ai++;
        model = (new SuffixSensitiveGISModelReader(new File(args[ai]))).getModel();
      }
      else {
        System.err.println("Invalid option " + args[ai]);
        System.exit(1);
      }
      ai++;
    }
    HeadRules rules = new opennlp.tools.parser.lang.en.HeadRules(args[ai++]);
    if (fun) {
      Parse.useFunctionTags(true);
    }
    ObjectStream<Event> es = new ParserEventStream(new ParseSampleStream(new PlainTextByLineStream(new java.io.InputStreamReader(System.in))), rules, etype, dict);
    Event e;
    while ((e = es.read()) != null) {
      if (model != null) {
        System.out.print(model.eval(e.getContext())[model.getIndex(e.getOutcome())]+" ");
      }
      System.out.println(e);
    }
  }
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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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    String lang = args[1];
    String packageName = args[2];
    String modelName = args[3];

    AbstractModel chunkerModel = new GenericModelReader(
        new BinaryFileDataReader(new FileInputStream(modelName))).getModel();

    ChunkerModel packageModel = new ChunkerModel(lang, chunkerModel);
    packageModel.serialize(new FileOutputStream(packageName));
  }
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      // TODO: Maybe that should be part of the ChunkingParser ...
      // Training build
      System.out.println("Training check model");
      ObjectStream<Event> bes = new ParserEventStream(parseSamples,
          originalModel.getHeadRules(), ParserEventTypeEnum.CHECK, mdict);
      AbstractModel checkModel = Parser.train(bes,
          100, 5);

      parseSamples.close();

      return originalModel.updateCheckModel(checkModel);
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  }

  public AbstractModel doTrain(DataIndexer indexer) throws IOException {
    int iterations = getIterations();

    AbstractModel model;

    int threads = getIntParam("Threads", 1);

    model = trainModel(iterations, indexer, true, false, null, 0, threads);
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      // TODO: training individual models should be in the chunking parser, not here
      // Training build
      System.out.println("Training builder");
      ObjectStream<Event> bes = new ParserEventStream(parseSamples,
          originalModel.getHeadRules(), ParserEventTypeEnum.BUILD, mdict);
      AbstractModel buildModel = Parser.train(bes,
          100, 5);

      parseSamples.close();

      return originalModel.updateBuildModel(buildModel);
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  public static void main(String[] args) throws java.io.IOException {
    if (args.length == 0) {
      System.err.println("Usage: GISModel modelname < contexts");
      System.exit(1);
    }
    AbstractModel m = new opennlp.tools.ml.maxent.io.SuffixSensitiveGISModelReader(
        new File(args[0])).getModel();
    BufferedReader in = new BufferedReader(new InputStreamReader(System.in));
    DecimalFormat df = new java.text.DecimalFormat(".###");
    for (String line = in.readLine(); line != null; line = in.readLine()) {
      String[] context = line.split(" ");
      double[] dist = m.eval(context);
      for (int oi = 0; oi < dist.length; oi++) {
        System.out.print("[" + m.getOutcome(oi) + " " + df.format(dist[oi])
            + "] ");
      }
      System.out.println();
    }
  }
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    }

    int iterations = getIterations();
    int cutoff = getCutoff();

    AbstractModel model;

    boolean useAverage = getBooleanParam("UseAverage", true);

    boolean useSkippedAveraging = getBooleanParam("UseSkippedAveraging", false);
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  public static void main(String[] args) throws java.io.IOException {
    if (args.length == 0) {
      System.err.println("Usage: PerceptronModel modelname < contexts");
      System.exit(1);
    }
    AbstractModel m = new PerceptronModelReader(new File(args[0])).getModel();
    BufferedReader in = new BufferedReader(new InputStreamReader(System.in));
    DecimalFormat df = new java.text.DecimalFormat(".###");
    for (String line = in.readLine(); line != null; line = in.readLine()) {
      String[] context = line.split(" ");
      double[] dist = m.eval(context);
      for (int oi=0;oi<dist.length;oi++) {
        System.out.print("["+m.getOutcome(oi)+" "+df.format(dist[oi])+"] ");
      }
      System.out.println();
    }
  }
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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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Related Classes of opennlp.tools.ml.model.AbstractModel

  • opennlp.tools.chunker.ChunkerModel
  • opennlp.tools.cmdline.parser.BuildModelUpdaterTool
  • opennlp.tools.cmdline.parser.CheckModelUpdaterTool
  • opennlp.tools.ml.maxent.GIS
  • opennlp.tools.ml.maxent.GISModel
  • opennlp.tools.ml.maxent.io.SuffixSensitiveGISModelReader
  • opennlp.tools.ml.maxent.MaxentPrepAttachTest
  • opennlp.tools.ml.maxent.quasinewton.QNPrepAttachTest
  • opennlp.tools.ml.maxent.quasinewton.QNTrainerTest
  • opennlp.tools.ml.perceptron.PerceptronModel
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