cc.mallet.types.Alphabet.clone()方法的使用及代码示例

x33g5p2x  于2022-01-16 转载在 其他  
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本文整理了Java中cc.mallet.types.Alphabet.clone()方法的一些代码示例，展示了Alphabet.clone()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。Alphabet.clone()方法的具体详情如下：
包路径：cc.mallet.types.Alphabet
类名称：Alphabet
方法名：clone

Alphabet.clone介绍

暂无

代码示例

代码示例来源：origin: cc.mallet/mallet

  1. private void copyStatesAndWeightsFrom (CRF initialCRF)
  2. {
  3.   this.parameters = new Factors (initialCRF.parameters, true);  // This will copy all the transition weights
  4.   this.parameters.weightAlphabet = (Alphabet) initialCRF.parameters.weightAlphabet.clone();
  5.   //weightAlphabet = (Alphabet) initialCRF.weightAlphabet.clone ();
  6.   //weights = new SparseVector [initialCRF.weights.length];
  7.   
  8.   states.clear ();
  9.   // Clear these, because they will be filled by this.addState()
  10.   this.parameters.initialWeights = new double[0];
  11.   this.parameters.finalWeights = new double[0];
  13.   for (int i = 0; i < initialCRF.states.size(); i++) {
  14.     State s = (State) initialCRF.getState (i);
  15.     String[][] weightNames = new String[s.weightsIndices.length][];
  16.     for (int j = 0; j < weightNames.length; j++) {
  17.       int[] thisW = s.weightsIndices[j];
  18.       weightNames[j] = (String[]) initialCRF.parameters.weightAlphabet.lookupObjects(thisW, new String [s.weightsIndices[j].length]);
  19.     }
  20.     addState (s.name, initialCRF.parameters.initialWeights[i], initialCRF.parameters.finalWeights[i], 
  21.         s.destinationNames, s.labels, weightNames);
  22.   }
  23.   featureSelections = initialCRF.featureSelections.clone ();
  24.   // yyy weightsFrozen = (boolean[]) initialCRF.weightsFrozen.clone();
  25. }

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

  1. /** Construct new Factors by copying the other one. */
  2. public Factors (Factors other, boolean cloneAlphabet) {
  3.   weightAlphabet = cloneAlphabet ? (Alphabet) other.weightAlphabet.clone() : other.weightAlphabet;
  4.   weights = new SparseVector[other.weights.length];
  5.   for (int i = 0; i < weights.length; i++)
  6.     weights[i] = (SparseVector) other.weights[i].cloneMatrix();
  7.   defaultWeights = other.defaultWeights.clone();
  8.   weightsFrozen = other.weightsFrozen;
  9.   initialWeights = other.initialWeights.clone();
  10.   finalWeights = other.finalWeights.clone();
  11. }

代码示例来源：origin: cc.mallet/mallet

  1. /** Construct new Factors by copying the other one. */
  2. public Factors (Factors other, boolean cloneAlphabet) {
  3.   weightAlphabet = cloneAlphabet ? (Alphabet) other.weightAlphabet.clone() : other.weightAlphabet;
  4.   weights = new SparseVector[other.weights.length];
  5.   for (int i = 0; i < weights.length; i++)
  6.     weights[i] = (SparseVector) other.weights[i].cloneMatrix();
  7.   defaultWeights = other.defaultWeights.clone();
  8.   weightsFrozen = other.weightsFrozen;
  9.   initialWeights = other.initialWeights.clone();
  10.   finalWeights = other.finalWeights.clone();
  11. }

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

  1. /** Construct new Factors by copying the other one. */
  2. public Factors (Factors other, boolean cloneAlphabet) {
  3.   weightAlphabet = cloneAlphabet ? (Alphabet) other.weightAlphabet.clone() : other.weightAlphabet;
  4.   weights = new SparseVector[other.weights.length];
  5.   for (int i = 0; i < weights.length; i++)
  6.     weights[i] = (SparseVector) other.weights[i].cloneMatrix();
  7.   defaultWeights = other.defaultWeights.clone();
  8.   weightsFrozen = other.weightsFrozen;
  9.   initialWeights = other.initialWeights.clone();
  10.   finalWeights = other.finalWeights.clone();
  11. }

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

  1. private void copyStatesAndWeightsFrom (CRF initialCRF)
  2. {
  3.   this.parameters = new Factors (initialCRF.parameters, true);  // This will copy all the transition weights
  4.   this.parameters.weightAlphabet = (Alphabet) initialCRF.parameters.weightAlphabet.clone();
  5.   //weightAlphabet = (Alphabet) initialCRF.weightAlphabet.clone ();
  6.   //weights = new SparseVector [initialCRF.weights.length];
  7.   
  8.   states.clear ();
  9.   // Clear these, because they will be filled by this.addState()
  10.   this.parameters.initialWeights = new double[0];
  11.   this.parameters.finalWeights = new double[0];
  13.   for (int i = 0; i < initialCRF.states.size(); i++) {
  14.     State s = (State) initialCRF.getState (i);
  15.     String[][] weightNames = new String[s.weightsIndices.length][];
  16.     for (int j = 0; j < weightNames.length; j++) {
  17.       int[] thisW = s.weightsIndices[j];
  18.       weightNames[j] = (String[]) initialCRF.parameters.weightAlphabet.lookupObjects(thisW, new String [s.weightsIndices[j].length]);
  19.     }
  20.     addState (s.name, initialCRF.parameters.initialWeights[i], initialCRF.parameters.finalWeights[i], 
  21.         s.destinationNames, s.labels, weightNames);
  22.   }
  23.   featureSelections = initialCRF.featureSelections.clone ();
  24.   // yyy weightsFrozen = (boolean[]) initialCRF.weightsFrozen.clone();
  25. }

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

  1. private void copyStatesAndWeightsFrom (CRF initialCRF)
  2. {
  3.   this.parameters = new Factors (initialCRF.parameters, true);  // This will copy all the transition weights
  4.   this.parameters.weightAlphabet = (Alphabet) initialCRF.parameters.weightAlphabet.clone();
  5.   //weightAlphabet = (Alphabet) initialCRF.weightAlphabet.clone ();
  6.   //weights = new SparseVector [initialCRF.weights.length];
  7.   
  8.   states.clear ();
  9.   // Clear these, because they will be filled by this.addState()
  10.   this.parameters.initialWeights = new double[0];
  11.   this.parameters.finalWeights = new double[0];
  13.   for (int i = 0; i < initialCRF.states.size(); i++) {
  14.     State s = (State) initialCRF.getState (i);
  15.     String[][] weightNames = new String[s.weightsIndices.length][];
  16.     for (int j = 0; j < weightNames.length; j++) {
  17.       int[] thisW = s.weightsIndices[j];
  18.       weightNames[j] = (String[]) initialCRF.parameters.weightAlphabet.lookupObjects(thisW, new String [s.weightsIndices[j].length]);
  19.     }
  20.     addState (s.name, initialCRF.parameters.initialWeights[i], initialCRF.parameters.finalWeights[i], 
  21.         s.destinationNames, s.labels, weightNames);
  22.   }
  23.   featureSelections = initialCRF.featureSelections.clone ();
  24.   // yyy weightsFrozen = (boolean[]) initialCRF.weightsFrozen.clone();
  25. }

代码示例来源：origin: cc.mallet/mallet

  1. public AddClassifierTokenPredictions(TokenClassifiers tokenClassifiers, int[] predRanks2add, 
  2.     boolean binary, InstanceList testList)
  3. {
  4.   m_predRanks2add = predRanks2add;
  5.   m_binary = binary;
  6.   m_tokenClassifiers = tokenClassifiers;
  7.   m_inProduction = false;
  8.   m_dataAlphabet = (Alphabet) tokenClassifiers.getAlphabet().clone();
  9.   Alphabet labelAlphabet = tokenClassifiers.getLabelAlphabet();
  10.   
  11.   // add the token prediction features to the alphabet
  12.   for (int i = 0; i < m_predRanks2add.length; i++) {
  13.     for (int j = 0; j < labelAlphabet.size(); j++) {
  14.       String featName = "TOK_PRED=" + labelAlphabet.lookupObject(j).toString() + "_@_RANK_" + m_predRanks2add[i];
  15.       m_dataAlphabet.lookupIndex(featName, true);
  16.     }
  17.   }
  18.   
  19.   // evaluate token classifier  
  20.   if (testList != null) {
  21.     Trial trial = new Trial(m_tokenClassifiers, testList);
  22.     logger.info("Token classifier accuracy on test set = " + trial.getAccuracy());
  23.   }
  24. }

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

  1. public AddClassifierTokenPredictions(TokenClassifiers tokenClassifiers, int[] predRanks2add, 
  2.     boolean binary, InstanceList testList)
  3. {
  4.   m_predRanks2add = predRanks2add;
  5.   m_binary = binary;
  6.   m_tokenClassifiers = tokenClassifiers;
  7.   m_inProduction = false;
  8.   m_dataAlphabet = (Alphabet) tokenClassifiers.getAlphabet().clone();
  9.   Alphabet labelAlphabet = tokenClassifiers.getLabelAlphabet();
  10.   
  11.   // add the token prediction features to the alphabet
  12.   for (int i = 0; i < m_predRanks2add.length; i++) {
  13.     for (int j = 0; j < labelAlphabet.size(); j++) {
  14.       String featName = "TOK_PRED=" + labelAlphabet.lookupObject(j).toString() + "_@_RANK_" + m_predRanks2add[i];
  15.       m_dataAlphabet.lookupIndex(featName, true);
  16.     }
  17.   }
  18.   
  19.   // evaluate token classifier  
  20.   if (testList != null) {
  21.     Trial trial = new Trial(m_tokenClassifiers, testList);
  22.     logger.info("Token classifier accuracy on test set = " + trial.getAccuracy());
  23.   }
  24. }

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

  1. public AddClassifierTokenPredictions(TokenClassifiers tokenClassifiers, int[] predRanks2add, 
  2.     boolean binary, InstanceList testList)
  3. {
  4.   m_predRanks2add = predRanks2add;
  5.   m_binary = binary;
  6.   m_tokenClassifiers = tokenClassifiers;
  7.   m_inProduction = false;
  8.   m_dataAlphabet = (Alphabet) tokenClassifiers.getAlphabet().clone();
  9.   Alphabet labelAlphabet = tokenClassifiers.getLabelAlphabet();
  10.   
  11.   // add the token prediction features to the alphabet
  12.   for (int i = 0; i < m_predRanks2add.length; i++) {
  13.     for (int j = 0; j < labelAlphabet.size(); j++) {
  14.       String featName = "TOK_PRED=" + labelAlphabet.lookupObject(j).toString() + "_@_RANK_" + m_predRanks2add[i];
  15.       m_dataAlphabet.lookupIndex(featName, true);
  16.     }
  17.   }
  18.   
  19.   // evaluate token classifier  
  20.   if (testList != null) {
  21.     Trial trial = new Trial(m_tokenClassifiers, testList);
  22.     logger.info("Token classifier accuracy on test set = " + trial.getAccuracy());
  23.   }
  24. }

代码示例来源：origin: cc.mallet/mallet

  1. return;
  2. Alphabet tmpDV = (Alphabet) ilist.getDataAlphabet().clone();
  3. FeatureSelection featuresSelected = ilist.getFeatureSelection();
  4. InstanceList tmpilist = new InstanceList (tmpDV, ilist.getTargetAlphabet());

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

  1. return;
  2. Alphabet tmpDV = (Alphabet) ilist.getDataAlphabet().clone();
  3. FeatureSelection featuresSelected = ilist.getFeatureSelection();
  4. InstanceList tmpilist = new InstanceList (tmpDV, ilist.getTargetAlphabet());

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

  1. return;
  2. Alphabet tmpDV = (Alphabet) ilist.getDataAlphabet().clone();
  3. FeatureSelection featuresSelected = ilist.getFeatureSelection();
  4. InstanceList tmpilist = new InstanceList (tmpDV, ilist.getTargetAlphabet());

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