Package opennlp.model

Examples of opennlp.model.MutableContext

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          for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
            outcomePattern[aoi] = activeOutcomes[aoi];
          }
        }
      }
      params[pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      for (int i = 0; i< modelExpects.length; i++)
        modelExpects[i][pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      observedExpects[pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
        int oi = outcomePattern[aoi];
        params[pi].setParameter(aoi, 0.0);
        for (int i = 0; i< modelExpects.length; i++)
          modelExpects[i][pi].setParameter(aoi, 0.0);
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    for (int oi = 0; oi < numOutcomes; oi++) {
      allOutcomesPattern[oi] = oi;
    }
   
    for (int pi = 0; pi < numPreds; pi++) {
      params[pi]=new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      if (useAverage) averageParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      for (int aoi=0;aoi<numOutcomes;aoi++) {
        params[pi].setParameter(aoi, 0.0);
        if (useAverage) averageParams[pi].setParameter(aoi, 0.0);
      }
    }
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      allOutcomesPattern[oi] = oi;

    /** Stores the estimated parameter value of each predicate during iteration. */
    MutableContext[] params = new MutableContext[numPreds];
    for (int pi = 0; pi < numPreds; pi++) {
      params[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      for (int aoi=0;aoi<numOutcomes;aoi++)
        params[pi].setParameter(aoi, 0.0);
    }

    EvalParameters evalParams = new EvalParameters(params,numOutcomes);
 
    /** Stores the sum of parameter values of each predicate over many iterations. */
    MutableContext[] summedParams = new MutableContext[numPreds];
    if (useAverage) {
      for (int pi = 0; pi < numPreds; pi++) {
        summedParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
        for (int aoi=0;aoi<numOutcomes;aoi++)
          summedParams[pi].setParameter(aoi, 0.0);
      }
    }

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      allOutcomesPattern[oi] = oi;

    /** Stores the estimated parameter value of each predicate during iteration. */
    MutableContext[] params = new MutableContext[numPreds];
    for (int pi = 0; pi < numPreds; pi++) {
      params[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      for (int aoi=0;aoi<numOutcomes;aoi++)
        params[pi].setParameter(aoi, 0.0);
    }

    EvalParameters evalParams = new EvalParameters(params,numOutcomes);
 
    /** Stores the sum of parameter values of each predicate over many iterations. */
    MutableContext[] summedParams = new MutableContext[numPreds];
    if (useAverage) {
      for (int pi = 0; pi < numPreds; pi++) {
        summedParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
        for (int aoi=0;aoi<numOutcomes;aoi++)
          summedParams[pi].setParameter(aoi, 0.0);
      }
    }

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          for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
            outcomePattern[aoi] = activeOutcomes[aoi];
          }
        }
      }
      params[pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      for (int i = 0; i< modelExpects.length; i++)
        modelExpects[i][pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      observedExpects[pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
        int oi = outcomePattern[aoi];
        params[pi].setParameter(aoi, 0.0);
        for (MutableContext[] modelExpect : modelExpects) {
          modelExpect[pi].setParameter(aoi, 0.0);
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    for (int oi = 0; oi < numOutcomes; oi++) {
      allOutcomesPattern[oi] = oi;
    }
   
    for (int pi = 0; pi < numPreds; pi++) {
      params[pi]=new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      if (useAverage) averageParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      for (int aoi=0;aoi<numOutcomes;aoi++) {
        params[pi].setParameter(aoi, 0.0);
        if (useAverage) averageParams[pi].setParameter(aoi, 0.0);
      }
    }
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    for (int oi = 0; oi < numOutcomes; oi++) {
      allOutcomesPattern[oi] = oi;
    }
   
    for (int pi = 0; pi < numPreds; pi++) {
      params[pi]=new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      if (useAverage) averageParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      for (int aoi=0;aoi<numOutcomes;aoi++) {
        params[pi].setParameter(aoi, 0.0);
        if (useAverage) averageParams[pi].setParameter(aoi, 0.0);
      }
    }
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    for (int oi = 0; oi < numOutcomes; oi++) {
      allOutcomesPattern[oi] = oi;
    }
   
    for (int pi = 0; pi < numPreds; pi++) {
      params[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
      if (useAverage)
        averageParams[pi] = new MutableContext(allOutcomesPattern,new double[numOutcomes]);
        for (int aoi=0;aoi<numOutcomes;aoi++) {
          params[pi].setParameter(aoi, 0.0);
          if (useAverage)
            averageParams[pi].setParameter(aoi, 0.0);
        }
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          for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
            outcomePattern[aoi] = activeOutcomes[aoi];
          }
        }
      }
      params[pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      modelExpects[pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      observedExpects[pi] = new MutableContext(outcomePattern,new double[numActiveOutcomes]);
      for (int aoi=0;aoi<numActiveOutcomes;aoi++) {
        int oi = outcomePattern[aoi];
        params[pi].setParameter(aoi, 0.0);
        modelExpects[pi].setParameter(aoi, 0.0);
        if (predCount[pi][oi] > 0) {
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Related Classes of opennlp.model.MutableContext

  • opennlp.maxent.GISTrainer
  • opennlp.perceptron.PerceptronTrainer
  • opennlp.perceptron.SimplePerceptronSequenceTrainer
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