Java FeatureVectorSequence.getFeatureVector方法代码示例

本文整理汇总了Java中cc.mallet.types.FeatureVectorSequence.getFeatureVector方法的典型用法代码示例。如果您正苦于以下问题：Java FeatureVectorSequence.getFeatureVector方法的具体用法？Java FeatureVectorSequence.getFeatureVector怎么用？Java FeatureVectorSequence.getFeatureVector使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cc.mallet.types.FeatureVectorSequence的用法示例。

在下文中一共展示了FeatureVectorSequence.getFeatureVector方法的7个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。

示例1: computeExpectations

import cc.mallet.types.FeatureVectorSequence; //导入方法依赖的package包/类
public void computeExpectations(ArrayList<SumLattice> lattices) {
  double[][][] xis;
  TIntArrayList cache = new TIntArrayList();
  for (int i = 0; i < lattices.size(); i++) {
    if (lattices.get(i) == null) { continue; }
    FeatureVectorSequence fvs = (FeatureVectorSequence)lattices.get(i).getInput();
    SumLattice lattice = lattices.get(i);
    xis = lattice.getXis();
    for (int ip = 1; ip < fvs.size(); ++ip) {
      cache.resetQuick();
      FeatureVector fv = fvs.getFeatureVector(ip);
      int fi;
      for (int loc = 0; loc < fv.numLocations(); loc++) {
        fi = fv.indexAtLocation(loc);
        // binary constraint features
        if (constraintsMap.containsKey(fi)) {
          cache.add(constraintsMap.get(fi));
        }
      }
      for (int prev = 0; prev < map.getNumStates(); ++prev) {
        int liPrev = map.getLabelIndex(prev);
        if (liPrev != StateLabelMap.START_LABEL) {
          for (int curr = 0; curr < map.getNumStates(); ++curr) {
            int liCurr = map.getLabelIndex(curr);
            if (liCurr != StateLabelMap.START_LABEL) {
              double prob = Math.exp(xis[ip][prev][curr]);
              for (int j = 0; j < cache.size(); j++) {
                constraintsList.get(cache.getQuick(j)).expectation[liPrev][liCurr] += prob;
              }
            }
          }
        }
      }
    }
  }
}

开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:37，代码来源:TwoLabelGEConstraints.java

示例2: computeExpectations

import cc.mallet.types.FeatureVectorSequence; //导入方法依赖的package包/类
public void computeExpectations(ArrayList<SumLattice> lattices) {
  double[][] gammas;    
  TIntArrayList cache = new TIntArrayList();
  for (int i = 0; i < lattices.size(); i++) {
    if (lattices.get(i) == null) { continue; }
    SumLattice lattice = lattices.get(i);
    FeatureVectorSequence fvs = (FeatureVectorSequence)lattice.getInput();
    gammas = lattice.getGammas();
    for (int ip = 0; ip < fvs.size(); ++ip) {
      cache.resetQuick();
      FeatureVector fv = fvs.getFeatureVector(ip);
      int fi;
      for (int loc = 0; loc < fv.numLocations(); loc++) {
        fi = fv.indexAtLocation(loc);
        // binary constraint features
        if (constraints.containsKey(fi)) {
          cache.add(fi);
        }
      }
      if (constraints.containsKey(fv.getAlphabet().size())) {
        cache.add(fv.getAlphabet().size());
      }
      for (int s = 0; s < map.getNumStates(); ++s) {
        int li = map.getLabelIndex(s);
        if (li != StateLabelMap.START_LABEL) {
          double gammaProb = Math.exp(gammas[ip+1][s]);
          for (int j = 0; j < cache.size(); j++) {
            constraints.get(cache.getQuick(j)).incrementExpectation(li,gammaProb);
          }
        }
      }
    }
  }
}

开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:35，代码来源:OneLabelL2RangeGEConstraints.java

示例3: computeExpectations

import cc.mallet.types.FeatureVectorSequence; //导入方法依赖的package包/类
public void computeExpectations(ArrayList<SumLattice> lattices) {
  double[][] gammas;    
  TIntArrayList cache = new TIntArrayList();
  for (int i = 0; i < lattices.size(); i++) {
    if (lattices.get(i) == null) { continue; }
    SumLattice lattice = lattices.get(i);
    FeatureVectorSequence fvs = (FeatureVectorSequence)lattice.getInput();
    gammas = lattice.getGammas();
    for (int ip = 0; ip < fvs.size(); ++ip) {
      cache.resetQuick();
      FeatureVector fv = fvs.getFeatureVector(ip);
      int fi;
      for (int loc = 0; loc < fv.numLocations(); loc++) {
        fi = fv.indexAtLocation(loc);
        // binary constraint features
        if (constraints.containsKey(fi)) {
          cache.add(fi);
        }
      }
      if (constraints.containsKey(fv.getAlphabet().size())) {
        cache.add(fv.getAlphabet().size());
      }
      for (int s = 0; s < map.getNumStates(); ++s) {
        int li = map.getLabelIndex(s);
        if (li != StateLabelMap.START_LABEL) {
          double gammaProb = Math.exp(gammas[ip+1][s]);
          for (int j = 0; j < cache.size(); j++) {
            constraints.get(cache.getQuick(j)).expectation[li] += gammaProb;
          }
        }
      }
    }
  }
}

开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:35，代码来源:OneLabelGEConstraints.java

示例4: convert

import cc.mallet.types.FeatureVectorSequence; //导入方法依赖的package包/类
/**
 * 
 * @param inst input instance, with FeatureVectorSequence as data.
 * @param alphabetsPipe a Noop pipe containing the data and target alphabets for 
 * the resulting InstanceList and AugmentableFeatureVectors
 * @return list of instances, each with one AugmentableFeatureVector as data
 */
public static InstanceList convert(Instance inst, Noop alphabetsPipe)
{
	InstanceList ret = new InstanceList(alphabetsPipe);
	Object obj = inst.getData();
	assert(obj instanceof FeatureVectorSequence);

	FeatureVectorSequence fvs = (FeatureVectorSequence) obj;
	LabelSequence ls = (LabelSequence) inst.getTarget();
	assert(fvs.size() == ls.size());

	Object instName = (inst.getName() == null ? "NONAME" : inst.getName());
	
	for (int j = 0; j < fvs.size(); j++) {
		FeatureVector fv = fvs.getFeatureVector(j);
		int[] indices = fv.getIndices();
		FeatureVector data = new AugmentableFeatureVector (alphabetsPipe.getDataAlphabet(),
				indices, fv.getValues(), indices.length); 
		Labeling target = ls.getLabelAtPosition(j);
		String name = instName.toString() + "[email protected]_POS_" + (j + 1);
		Object source = inst.getSource();
		Instance toAdd = alphabetsPipe.pipe(new Instance(data, target, name, source));

		ret.add(toAdd);
	}

	return ret;
}

开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:35，代码来源:AddClassifierTokenPredictions.java

示例5: computeExpectations

import cc.mallet.types.FeatureVectorSequence; //导入方法依赖的package包/类
public void computeExpectations(ArrayList<SumLattice> lattices) {
  double[][][] xis;
  IntArrayList cache = new IntArrayList();
  for (int i = 0; i < lattices.size(); i++) {
    if (lattices.get(i) == null) { continue; }
    FeatureVectorSequence fvs = (FeatureVectorSequence)lattices.get(i).getInput();
    SumLattice lattice = lattices.get(i);
    xis = lattice.getXis();
    for (int ip = 1; ip < fvs.size(); ++ip) {
      cache.clear();
      FeatureVector fv = fvs.getFeatureVector(ip);
      int fi;
      for (int loc = 0; loc < fv.numLocations(); loc++) {
        fi = fv.indexAtLocation(loc);
        // binary constraint features
        if (constraintsMap.containsKey(fi)) {
          cache.add(constraintsMap.get(fi));
        }
      }
      for (int prev = 0; prev < map.getNumStates(); ++prev) {
        int liPrev = map.getLabelIndex(prev);
        if (liPrev != StateLabelMap.START_LABEL) {
          for (int curr = 0; curr < map.getNumStates(); ++curr) {
            int liCurr = map.getLabelIndex(curr);
            if (liCurr != StateLabelMap.START_LABEL) {
              double prob = Math.exp(xis[ip][prev][curr]);
              for (int j = 0; j < cache.size(); j++) {
                constraintsList.get(cache.get(j)).expectation[liPrev][liCurr] += prob;
              }
            }
          }
        }
      }
    }
  }
}

开发者ID:cmoen，项目名称:mallet，代码行数:37，代码来源:TwoLabelGEConstraints.java

示例6: computeExpectations

import cc.mallet.types.FeatureVectorSequence; //导入方法依赖的package包/类
public void computeExpectations(ArrayList<SumLattice> lattices) {
  double[][] gammas;    
  IntArrayList cache = new IntArrayList();
  for (int i = 0; i < lattices.size(); i++) {
    if (lattices.get(i) == null) { continue; }
    SumLattice lattice = lattices.get(i);
    FeatureVectorSequence fvs = (FeatureVectorSequence)lattice.getInput();
    gammas = lattice.getGammas();
    for (int ip = 0; ip < fvs.size(); ++ip) {
      cache.clear();
      FeatureVector fv = fvs.getFeatureVector(ip);
      int fi;
      for (int loc = 0; loc < fv.numLocations(); loc++) {
        fi = fv.indexAtLocation(loc);
        // binary constraint features
        if (constraints.containsKey(fi)) {
          cache.add(fi);
        }
      }
      if (constraints.containsKey(fv.getAlphabet().size())) {
        cache.add(fv.getAlphabet().size());
      }
      for (int s = 0; s < map.getNumStates(); ++s) {
        int li = map.getLabelIndex(s);
        if (li != StateLabelMap.START_LABEL) {
          double gammaProb = Math.exp(gammas[ip+1][s]);
          for (int j = 0; j < cache.size(); j++) {
            constraints.get(cache.get(j)).incrementExpectation(li,gammaProb);
          }
        }
      }
    }
  }
}

开发者ID:cmoen，项目名称:mallet，代码行数:35，代码来源:OneLabelL2RangeGEConstraints.java

示例7: computeExpectations

import cc.mallet.types.FeatureVectorSequence; //导入方法依赖的package包/类
public void computeExpectations(ArrayList<SumLattice> lattices) {
  double[][] gammas;    
  IntArrayList cache = new IntArrayList();
  for (int i = 0; i < lattices.size(); i++) {
    if (lattices.get(i) == null) { continue; }
    SumLattice lattice = lattices.get(i);
    FeatureVectorSequence fvs = (FeatureVectorSequence)lattice.getInput();
    gammas = lattice.getGammas();
    for (int ip = 0; ip < fvs.size(); ++ip) {
      cache.clear();
      FeatureVector fv = fvs.getFeatureVector(ip);
      int fi;
      for (int loc = 0; loc < fv.numLocations(); loc++) {
        fi = fv.indexAtLocation(loc);
        // binary constraint features
        if (constraints.containsKey(fi)) {
          cache.add(fi);
        }
      }
      if (constraints.containsKey(fv.getAlphabet().size())) {
        cache.add(fv.getAlphabet().size());
      }
      for (int s = 0; s < map.getNumStates(); ++s) {
        int li = map.getLabelIndex(s);
        if (li != StateLabelMap.START_LABEL) {
          double gammaProb = Math.exp(gammas[ip+1][s]);
          for (int j = 0; j < cache.size(); j++) {
            constraints.get(cache.get(j)).expectation[li] += gammaProb;
          }
        }
      }
    }
  }
}

开发者ID:cmoen，项目名称:mallet，代码行数:35，代码来源:OneLabelGEConstraints.java

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