Package opennlp.tools.chunker

Examples of opennlp.tools.chunker.ChunkerEvaluator

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    if(params.getDetailedF()) {
      detailedFMeasureListener = new ChunkerDetailedFMeasureListener();
      listeners.add(detailedFMeasureListener);
    }

    ChunkerEvaluator evaluator = new ChunkerEvaluator(new ChunkerME(model,
        ChunkerME.DEFAULT_BEAM_SIZE, new DefaultChunkerSequenceValidator()),
        listeners.toArray(new ChunkerEvaluationMonitor[listeners.size()]));
   
    final ObjectStream<ChunkSample> sampleStream = ChunkerTrainerTool.openSampleData("Test",
        testData, encoding);

    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<ChunkSample> measuredSampleStream = new ObjectStream<ChunkSample>() {

      public ChunkSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      System.err.println("Reading test data error " + e.getMessage());
      throw new TerminateToolException(-1);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    if (detailedFMeasureListener == null) {
      System.out.println(evaluator.getFMeasure());
    } else {
      System.out.println(detailedFMeasureListener.toString());
    }
  }
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    if(params.getDetailedF()) {
      detailedFMeasureListener = new ChunkerDetailedFMeasureListener();
      listeners.add(detailedFMeasureListener);
    }

    ChunkerEvaluator evaluator = new ChunkerEvaluator(new ChunkerME(model,
        ChunkerME.DEFAULT_BEAM_SIZE),
        listeners.toArray(new ChunkerEvaluationMonitor[listeners.size()]));
   
    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<ChunkSample> measuredSampleStream = new ObjectStream<ChunkSample>() {

      public ChunkSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      throw new TerminateToolException(-1, "IO error while reading test data: " + e.getMessage(), e);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    if (detailedFMeasureListener == null) {
      System.out.println(evaluator.getFMeasure());
    } else {
      System.out.println(detailedFMeasureListener.toString());
    }
  }
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    if(params.getDetailedF()) {
      detailedFMeasureListener = new ChunkerDetailedFMeasureListener();
      listeners.add(detailedFMeasureListener);
    }

    ChunkerEvaluator evaluator = new ChunkerEvaluator(new ChunkerME(model,
        ChunkerME.DEFAULT_BEAM_SIZE),
        listeners.toArray(new ChunkerEvaluationMonitor[listeners.size()]));

    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<ChunkSample> measuredSampleStream = new ObjectStream<ChunkSample>() {

      public ChunkSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      throw new TerminateToolException(-1, "IO error while reading test data: " + e.getMessage(), e);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    if (detailedFMeasureListener == null) {
      System.out.println(evaluator.getFMeasure());
    } else {
      System.out.println(detailedFMeasureListener.toString());
    }
  }
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      throw new TerminateToolException(1);
    }

    ChunkerModel model = new ChunkerModelLoader().load(new File(params.getModel()));

    ChunkerEvaluator evaluator = new ChunkerEvaluator(new ChunkerME(model));
   
    final ObjectStream<ChunkSample> sampleStream = ChunkerTrainerTool.openSampleData("Test",
        testData, encoding);

    final PerformanceMonitor monitor = new PerformanceMonitor("sent");

    ObjectStream<ChunkSample> measuredSampleStream = new ObjectStream<ChunkSample>() {

      public ChunkSample read() throws IOException {
        monitor.incrementCounter();
        return sampleStream.read();
      }

      public void reset() throws IOException {
        sampleStream.reset();
      }

      public void close() throws IOException {
        sampleStream.close();
      }
    };

    monitor.startAndPrintThroughput();

    try {
      evaluator.evaluate(measuredSampleStream);
    } catch (IOException e) {
      System.err.println("failed");
      System.err.println("Reading test data error " + e.getMessage());
      throw new TerminateToolException(-1);
    } finally {
      try {
        measuredSampleStream.close();
      } catch (IOException e) {
        // sorry that this can fail
      }
    }

    monitor.stopAndPrintFinalResult();

    System.out.println();

    System.out.println(evaluator.getFMeasure());
  }
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Related Classes of opennlp.tools.chunker.ChunkerEvaluator

  • opennlp.tools.cmdline.chunker.ChunkerEvaluatorTool
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