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Java MEMMTrainer类代码示例

本文整理汇总了Java中cc.mallet.fst.MEMMTrainer类的典型用法代码示例。如果您正苦于以下问题：Java MEMMTrainer类的具体用法？Java MEMMTrainer怎么用？Java MEMMTrainer使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。


MEMMTrainer类属于cc.mallet.fst包，在下文中一共展示了MEMMTrainer类的8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: testGetSetParameters

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
public void testGetSetParameters()
{
  int inputVocabSize = 100;
  int numStates = 5;
  Alphabet inputAlphabet = new Alphabet();
  for (int i = 0; i < inputVocabSize; i++)
    inputAlphabet.lookupIndex("feature" + i);
  Alphabet outputAlphabet = new Alphabet();
  MEMM memm = new MEMM (inputAlphabet, outputAlphabet);
  String[] stateNames = new String[numStates];
  for (int i = 0; i < numStates; i++)
    stateNames[i] = "state" + i;
  memm.addFullyConnectedStates(stateNames);
  MEMMTrainer memmt = new MEMMTrainer (memm);
  MEMMTrainer.MEMMOptimizableByLabelLikelihood omemm = memmt.getOptimizableMEMM (new InstanceList(null));
  TestOptimizable.testGetSetParameters(omemm);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:18，代码来源:TestMEMM.java

示例2: testSpaceSerializable

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
public void testSpaceSerializable () throws IOException, ClassNotFoundException
{
  Pipe p = makeSpacePredictionPipe ();
  InstanceList training = new InstanceList (p);
  training.addThruPipe (new ArrayIterator (data));

  MEMM memm = new MEMM (p, null);
  memm.addFullyConnectedStatesForLabels ();
  memm.addStartState();
  memm.setWeightsDimensionAsIn(training);
 MEMMTrainer memmt = new MEMMTrainer (memm);
  memmt.train (training, 10);

  MEMM memm2 = (MEMM) TestSerializable.cloneViaSerialization (memm);

  Optimizable.ByGradientValue mcrf1 = memmt.getOptimizableMEMM(training);
  double val1 = mcrf1.getValue ();
  Optimizable.ByGradientValue mcrf2 = memmt.getOptimizableMEMM(training);
  double val2 = mcrf2.getValue ();

  assertEquals (val1, val2, 1e-5);
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:23，代码来源:TestMEMM.java

示例3: disabledtestPrint

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
public void disabledtestPrint ()
{
	Pipe p = new SerialPipes (new Pipe[] {
     new CharSequence2TokenSequence("."),
		 new TokenText(),
		 new TestMEMM.TestMEMMTokenSequenceRemoveSpaces(),
		 new TokenSequence2FeatureVectorSequence(),
		 new PrintInputAndTarget(),
  });
	InstanceList one = new InstanceList (p);
	String[] data = new String[] { "ABCDE", };
	one.addThruPipe (new ArrayIterator (data));
	MEMM crf = new MEMM (p, null);
	crf.addFullyConnectedStatesForLabels();
	crf.setWeightsDimensionAsIn (one);
	MEMMTrainer memmt = new MEMMTrainer (crf);
	MEMMTrainer.MEMMOptimizableByLabelLikelihood mcrf = memmt.getOptimizableMEMM(one);
	double[] params = new double[mcrf.getNumParameters()];
	for (int i = 0; i < params.length; i++) {
		params [i] = i;
	}
	mcrf.setParameters (params);
	crf.print ();
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:25，代码来源:TestMEMM.java

示例4: disabledtestPrint

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
public void disabledtestPrint ()
{
	Pipe p = new SerialPipes (new Pipe[] {
     new CharSequence2TokenSequence("."),
		 new TokenText(),
		 new TestMEMMTokenSequenceRemoveSpaces(),
		 new TokenSequence2FeatureVectorSequence(),
		 new PrintInputAndTarget(),
  });
	InstanceList one = new InstanceList (p);
	String[] data = new String[] { "ABCDE", };
	one.addThruPipe (new ArrayIterator (data));
	MEMM crf = new MEMM (p, null);
	crf.addFullyConnectedStatesForLabels();
	crf.setWeightsDimensionAsIn (one);
	MEMMTrainer memmt = new MEMMTrainer (crf);
	MEMMTrainer.MEMMOptimizableByLabelLikelihood mcrf = memmt.getOptimizableMEMM(one);
	double[] params = new double[mcrf.getNumParameters()];
	for (int i = 0; i < params.length; i++) {
		params [i] = i;
	}
	mcrf.setParameters (params);
	crf.print ();
}
开发者ID:shalomeir，项目名称:tctm，代码行数:25，代码来源:TestMEMM.java

示例5: ignoretestSpaceSerializable

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
public void ignoretestSpaceSerializable () throws IOException, ClassNotFoundException
{
  Pipe p = makeSpacePredictionPipe ();
  InstanceList training = new InstanceList (p);
  training.addThruPipe (new ArrayIterator (data));

  MEMM memm = new MEMM (p, null);
  memm.addFullyConnectedStatesForLabels ();
  memm.addStartState();
  memm.setWeightsDimensionAsIn(training);
 MEMMTrainer memmt = new MEMMTrainer (memm);
  memmt.train (training, 10);

  MEMM memm2 = (MEMM) TestSerializable.cloneViaSerialization (memm);

  Optimizable.ByGradientValue mcrf1 = memmt.getOptimizableMEMM(training);
  double val1 = mcrf1.getValue ();
  Optimizable.ByGradientValue mcrf2 = memmt.getOptimizableMEMM(training);
  double val2 = mcrf2.getValue ();

  assertEquals (val1, val2, 1e-5);
}
开发者ID:cmoen，项目名称:mallet，代码行数:23，代码来源:TestMEMM.java

示例6: testSpaceMaximizable

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
public void testSpaceMaximizable ()
  {
    Pipe p = makeSpacePredictionPipe ();
    InstanceList training = new InstanceList (p);
//    String[] data = { TestMEMM.data[0], }; // TestMEMM.data[1], TestMEMM.data[2], TestMEMM.data[3], };
//    String[] data = { "ab" };
    training.addThruPipe (new ArrayIterator (data));

//    CRF4 memm = new CRF4 (p, null);
    MEMM memm = new MEMM (p, null);
    memm.addFullyConnectedStatesForLabels ();
    memm.addStartState();
    memm.setWeightsDimensionAsIn(training);
    
	  MEMMTrainer memmt = new MEMMTrainer (memm);
//    memm.gatherTrainingSets (training); // ANNOYING: Need to set up per-instance training sets
    memmt.train (training, 1);  // Set weights dimension, gathers training sets, etc.

//    memm.print();
//    memm.printGradient = true;
//    memm.printInstanceLists();

//    memm.setGaussianPriorVariance (Double.POSITIVE_INFINITY);
    Optimizable.ByGradientValue mcrf = memmt.getOptimizableMEMM(training);
    TestOptimizable.setNumComponents (150);
    TestOptimizable.testValueAndGradient (mcrf);
  }
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:28，代码来源:TestMEMM.java

示例7: getLikelihood

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
double getLikelihood (MEMMTrainer memmt, InstanceList data) {
	Optimizable.ByGradientValue mcrf = memmt.getOptimizableMEMM(data);
	// Do this elaborate thing so that crf.cachedValueStale is forced true
	double[] params = new double [mcrf.getNumParameters()];
	mcrf.getParameters (params);
	mcrf.setParameters (params);
	return mcrf.getValue ();
}
开发者ID:kostagiolasn，项目名称:NucleosomePatternClassifier，代码行数:9，代码来源:TestMEMM.java

示例8: ignoretestSpaceMaximizable

import cc.mallet.fst.MEMMTrainer; //导入依赖的package包/类
public void ignoretestSpaceMaximizable ()
  {
    Pipe p = makeSpacePredictionPipe ();
    InstanceList training = new InstanceList (p);
//    String[] data = { TestMEMM.data[0], }; // TestMEMM.data[1], TestMEMM.data[2], TestMEMM.data[3], };
//    String[] data = { "ab" };
    training.addThruPipe (new ArrayIterator (data));

//    CRF4 memm = new CRF4 (p, null);
    MEMM memm = new MEMM (p, null);
    memm.addFullyConnectedStatesForLabels ();
    memm.addStartState();
    memm.setWeightsDimensionAsIn(training);
    
	  MEMMTrainer memmt = new MEMMTrainer (memm);
//    memm.gatherTrainingSets (training); // ANNOYING: Need to set up per-instance training sets
    memmt.train (training, 1);  // Set weights dimension, gathers training sets, etc.

//    memm.print();
//    memm.printGradient = true;
//    memm.printInstanceLists();

//    memm.setGaussianPriorVariance (Double.POSITIVE_INFINITY);
    Optimizable.ByGradientValue mcrf = memmt.getOptimizableMEMM(training);
    TestOptimizable.setNumComponents (150);
    TestOptimizable.testValueAndGradient (mcrf);
  }
开发者ID:cmoen，项目名称:mallet，代码行数:28，代码来源:TestMEMM.java


注：本文中的cc.mallet.fst.MEMMTrainer类示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。