本文整理了Java中cc.mallet.types.InstanceList.setPerLabelFeatureSelection()方法的一些代码示例，展示了InstanceList.setPerLabelFeatureSelection()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。InstanceList.setPerLabelFeatureSelection()方法的具体详情如下：
包路径：cc.mallet.types.InstanceList
类名称：InstanceList
方法名：setPerLabelFeatureSelection

InstanceList.setPerLabelFeatureSelection介绍

暂无

代码示例

代码示例来源：origin: cc.mallet/mallet

public void selectFeaturesForAllLabels (InstanceList ilist)
  
{
  RankedFeatureVector ranking = ranker.newRankedFeatureVector (ilist);
  FeatureSelection fs = new FeatureSelection (ilist.getDataAlphabet());
  if (numFeatures != -1) { // Select by number of features.
    int nf = Math.min (numFeatures, ranking.singleSize());
    for (int i = 0; i < nf; i++) {
      logger.info ("adding feature "+i+" word="+ilist.getDataAlphabet().lookupObject(ranking.getIndexAtRank(i)));
      fs.add (ranking.getIndexAtRank(i));
    }
  } else { // Select by threshold.
    for (int i = 0; i < ranking.singleSize(); i++) {
      if (ranking.getValueAtRank(i) > minThreshold)
        fs.add (ranking.getIndexAtRank(i));
    }
  }
  logger.info("Selected " + fs.cardinality() + " features from " +
              ilist.getDataAlphabet().size() + " features");
  ilist.setPerLabelFeatureSelection (null);
  ilist.setFeatureSelection (fs);
}

代码示例来源：origin: com.github.steveash.mallet/mallet

public void selectFeaturesForAllLabels (InstanceList ilist)
  
{
  RankedFeatureVector ranking = ranker.newRankedFeatureVector (ilist);
  FeatureSelection fs = new FeatureSelection (ilist.getDataAlphabet());
  if (numFeatures != -1) { // Select by number of features.
    int nf = Math.min (numFeatures, ranking.singleSize());
    for (int i = 0; i < nf; i++) {
      logger.info ("adding feature "+i+" word="+ilist.getDataAlphabet().lookupObject(ranking.getIndexAtRank(i)));
      fs.add (ranking.getIndexAtRank(i));
    }
  } else { // Select by threshold.
    for (int i = 0; i < ranking.singleSize(); i++) {
      if (ranking.getValueAtRank(i) > minThreshold)
        fs.add (ranking.getIndexAtRank(i));
    }
  }
  logger.info("Selected " + fs.cardinality() + " features from " +
              ilist.getDataAlphabet().size() + " features");
  ilist.setPerLabelFeatureSelection (null);
  ilist.setFeatureSelection (fs);
}

代码示例来源：origin: de.julielab/jcore-mallet-2.0.9

public void selectFeaturesForAllLabels (InstanceList ilist)
  
{
  RankedFeatureVector ranking = ranker.newRankedFeatureVector (ilist);
  FeatureSelection fs = new FeatureSelection (ilist.getDataAlphabet());
  if (numFeatures != -1) { // Select by number of features.
    int nf = Math.min (numFeatures, ranking.singleSize());
    for (int i = 0; i < nf; i++) {
      logger.info ("adding feature "+i+" word="+ilist.getDataAlphabet().lookupObject(ranking.getIndexAtRank(i)));
      fs.add (ranking.getIndexAtRank(i));
    }
  } else { // Select by threshold.
    for (int i = 0; i < ranking.singleSize(); i++) {
      if (ranking.getValueAtRank(i) > minThreshold)
        fs.add (ranking.getIndexAtRank(i));
    }
  }
  logger.info("Selected " + fs.cardinality() + " features from " +
              ilist.getDataAlphabet().size() + " features");
  ilist.setPerLabelFeatureSelection (null);
  ilist.setFeatureSelection (fs);
}

代码示例来源：origin: cc.mallet/mallet

public void selectFeaturesForPerLabel (InstanceList ilist)
{
  RankedFeatureVector[] rankings = perLabelRanker.newRankedFeatureVectors (ilist);
  int numClasses = rankings.length;
  FeatureSelection[] fs = new FeatureSelection[numClasses];
  for (int i = 0; i < numClasses; i++) {
    fs[i] = new FeatureSelection (ilist.getDataAlphabet());
    RankedFeatureVector ranking = rankings[i];
    int nf = Math.min (numFeatures, ranking.singleSize());
    if (nf >= 0) {
      for (int j = 0; j < nf; j++)
        fs[i].add (ranking.getIndexAtRank(j));
    } else {
      for (int j = 0; j < ranking.singleSize(); j++) {
        if (ranking.getValueAtRank(j) > minThreshold)
          fs[i].add (ranking.getIndexAtRank(j));
        else
          break;
      }
    }
  }
  ilist.setFeatureSelection (null);
  ilist.setPerLabelFeatureSelection (fs);
}

代码示例来源：origin: de.julielab/jcore-mallet-2.0.9

public void selectFeaturesForPerLabel (InstanceList ilist)
{
  RankedFeatureVector[] rankings = perLabelRanker.newRankedFeatureVectors (ilist);
  int numClasses = rankings.length;
  FeatureSelection[] fs = new FeatureSelection[numClasses];
  for (int i = 0; i < numClasses; i++) {
    fs[i] = new FeatureSelection (ilist.getDataAlphabet());
    RankedFeatureVector ranking = rankings[i];
    int nf = Math.min (numFeatures, ranking.singleSize());
    if (nf >= 0) {
      for (int j = 0; j < nf; j++)
        fs[i].add (ranking.getIndexAtRank(j));
    } else {
      for (int j = 0; j < ranking.singleSize(); j++) {
        if (ranking.getValueAtRank(j) > minThreshold)
          fs[i].add (ranking.getIndexAtRank(j));
        else
          break;
      }
    }
  }
  ilist.setFeatureSelection (null);
  ilist.setPerLabelFeatureSelection (fs);
}

代码示例来源：origin: com.github.steveash.mallet/mallet

public void selectFeaturesForPerLabel (InstanceList ilist)
{
  RankedFeatureVector[] rankings = perLabelRanker.newRankedFeatureVectors (ilist);
  int numClasses = rankings.length;
  FeatureSelection[] fs = new FeatureSelection[numClasses];
  for (int i = 0; i < numClasses; i++) {
    fs[i] = new FeatureSelection (ilist.getDataAlphabet());
    RankedFeatureVector ranking = rankings[i];
    int nf = Math.min (numFeatures, ranking.singleSize());
    if (nf >= 0) {
      for (int j = 0; j < nf; j++)
        fs[i].add (ranking.getIndexAtRank(j));
    } else {
      for (int j = 0; j < ranking.singleSize(); j++) {
        if (ranking.getValueAtRank(j) > minThreshold)
          fs[i].add (ranking.getIndexAtRank(j));
        else
          break;
      }
    }
  }
  ilist.setFeatureSelection (null);
  ilist.setPerLabelFeatureSelection (fs);
}