Package com.clearnlp.classification.train

Examples of com.clearnlp.classification.train.StringTrainSpace

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    LOG.debug("\n");
   
    mSize = lSpaces.get(0).length;
    spaces = new StringTrainSpace[mSize];
    StringTrainSpace sp;

    for (i=0; i<mSize; i++)
    {
      spaces[i] = lSpaces.get(0)[i];
     
      if ((size = lSpaces.size()) > 1)
      {
        LOG.info("Merging training instances:\n");
       
        for (j=1; j<size; j++)
        {
          spaces[i].appendSpace(sp = lSpaces.get(j)[i]);
          sp.clear();
          LOG.debug(".");
        }  LOG.debug("\n");
      }
    }
   
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  {
    int i, size = xmls.length;
    StringTrainSpace[] spaces = new StringTrainSpace[size];
   
    for (i=0; i<size; i++)
      spaces[i] = new StringTrainSpace(false, xmls[i].getLabelCutoff(cIndex), xmls[i].getFeatureCutoff(cIndex));
   
    return spaces;
  }
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  {
    StringTrainSpace[] spaces = new StringTrainSpace[size];
    int i;
   
    for (i=0; i<size; i++)
      spaces[i] = new StringTrainSpace(false, xml.getLabelCutoff(0), xml.getFeatureCutoff(0));
   
    return spaces;
  }
View Full Code Here
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    switch (vectorType)
    {
    case AbstractTrainSpace.VECTOR_SPARSE:
      space = new SparseTrainSpace(hasWeight); break;
    case AbstractTrainSpace.VECTOR_STRING:
      space = new StringTrainSpace(hasWeight, labelCutoff, featureCutoff); break;
    }
   
    space.readInstances(UTInput.createBufferedFileReader(trainFile));
    space.build();
   
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    switch (vectorType)
    {
    case AbstractTrainSpace.VECTOR_SPARSE:
      space = new SparseTrainSpace(hasWeight); break;
    case AbstractTrainSpace.VECTOR_STRING:
      space = new StringTrainSpace(hasWeight, labelCutoff, featureCutoff); break;
    }
   
    space.readInstances(UTInput.createBufferedFileReader(trainFile));
    space.build();
   
View Full Code Here
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    switch (vectorType)
    {
    case AbstractTrainSpace.VECTOR_SPARSE:
      space = new SparseTrainSpace(hasWeight); break;
    case AbstractTrainSpace.VECTOR_STRING:
      space = new StringTrainSpace(hasWeight, labelCutoff, featureCutoff); break;
    }
   
    space.readInstances(UTInput.createBufferedFileReader(trainFile));
    space.build();
   
View Full Code Here
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    switch (vectorType)
    {
    case AbstractTrainSpace.VECTOR_SPARSE:
      space = new SparseTrainSpace(hasWeight); break;
    case AbstractTrainSpace.VECTOR_STRING:
      space = new StringTrainSpace(hasWeight, labelCutoff, featureCutoff); break;
    }
   
    space.readInstances(UTInput.createBufferedFileReader(trainFile));
    space.build();
   
View Full Code Here
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    switch (vectorType)
    {
    case AbstractTrainSpace.VECTOR_SPARSE:
      space = new SparseTrainSpace(hasWeight); break;
    case AbstractTrainSpace.VECTOR_STRING:
      space = new StringTrainSpace(hasWeight, labelCutoff, featureCutoff); break;
    }
   
    space.readInstances(UTInput.createBufferedFileReader(trainFile));
    space.build();
   
View Full Code Here
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    LOG.debug("\n");
   
    mSize = lSpaces.get(0).length;
    spaces = new StringTrainSpace[mSize];
    StringTrainSpace sp;

    for (i=0; i<mSize; i++)
    {
      spaces[i] = lSpaces.get(0)[i];
     
      if ((size = lSpaces.size()) > 1)
      {
        LOG.info("Merging training instances:\n");
       
        for (j=1; j<size; j++)
        {
          spaces[i].appendSpace(sp = lSpaces.get(j)[i]);
          sp.clear();
          LOG.debug(".");
        }  LOG.debug("\n");
      }
    }
   
View Full Code Here
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  {
    int i, size = xmls.length;
    StringTrainSpace[] spaces = new StringTrainSpace[size];
   
    for (i=0; i<size; i++)
      spaces[i] = new StringTrainSpace(false, xmls[i].getLabelCutoff(cIndex), xmls[i].getFeatureCutoff(cIndex));
   
    return spaces;
  }
View Full Code Here
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Related Classes of com.clearnlp.classification.train.StringTrainSpace

  • com.clearnlp.classification.instance.StringInstance
  • com.clearnlp.classification.model.StringModel
  • com.clearnlp.classification.vector.SparseFeatureVector
  • com.clearnlp.classification.vector.StringFeatureVector
  • com.clearnlp.nlp.train.AbstractNLPTrainer
  • com.clearnlp.run.AbstractRun
  • com.clearnlp.run.AdaGradTrain
  • com.clearnlp.run.LiblinearTrain
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