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Java RandomTokenSequenceIterator类代码示例

原作者: [db:作者] 来自: [db:来源] 收藏 邀请

本文整理汇总了Java中cc.mallet.pipe.iterator.RandomTokenSequenceIterator的典型用法代码示例。如果您正苦于以下问题:Java RandomTokenSequenceIterator类的具体用法?Java RandomTokenSequenceIterator怎么用?Java RandomTokenSequenceIterator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。



RandomTokenSequenceIterator类属于cc.mallet.pipe.iterator包,在下文中一共展示了RandomTokenSequenceIterator类的4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,您的评价将有助于我们的系统推荐出更棒的Java代码示例。

示例1: InstanceList

import cc.mallet.pipe.iterator.RandomTokenSequenceIterator; //导入依赖的package包/类
/**
 * Creates a list consisting of randomly-generated
 * <code>FeatureVector</code>s.
 */
// xxx Perhaps split these out into a utility class
public InstanceList (Randoms r,
                     // the generator of all random-ness used here
                     Dirichlet classCentroidDistribution,
                     // includes a Alphabet
                     double classCentroidAverageAlphaMean,
                     // Gaussian mean on the sum of alphas
                     double classCentroidAverageAlphaVariance,
                     // Gaussian variance on the sum of alphas
                     double featureVectorSizePoissonLambda,
                     double classInstanceCountPoissonLambda,
                     String[] classNames)
{
	this (new SerialPipes (new Pipe[]	{
			new TokenSequence2FeatureSequence (),
			new FeatureSequence2FeatureVector (),
			new Target2Label()}));
	//classCentroidDistribution.print();
	Iterator<Instance> iter = new RandomTokenSequenceIterator (
			r, classCentroidDistribution,
			classCentroidAverageAlphaMean, classCentroidAverageAlphaVariance,
			featureVectorSizePoissonLambda, classInstanceCountPoissonLambda,
			classNames);
	this.addThruPipe (iter);
}
 
开发者ID:kostagiolasn,项目名称:NucleosomePatternClassifier,代码行数:30,代码来源:InstanceList.java


示例2: testRandomTrainedOn

import cc.mallet.pipe.iterator.RandomTokenSequenceIterator; //导入依赖的package包/类
private double testRandomTrainedOn (InstanceList training)
{
  ClassifierTrainer trainer = new MaxEntTrainer ();

  Alphabet fd = dictOfSize (3);
  String[] classNames = new String[] {"class0", "class1", "class2"};

  Randoms r = new Randoms (1);
  Iterator<Instance> iter = new RandomTokenSequenceIterator (r,  new Dirichlet(fd, 2.0),
        30, 0, 10, 200, classNames);
  training.addThruPipe (iter);

  InstanceList testing = new InstanceList (training.getPipe ());
  testing.addThruPipe (new RandomTokenSequenceIterator (r,  new Dirichlet(fd, 2.0),
        30, 0, 10, 200, classNames));

  System.out.println ("Training set size = "+training.size());
  System.out.println ("Testing set size = "+testing.size());

  Classifier classifier = trainer.train (training);

  System.out.println ("Accuracy on training set:");
  System.out.println (classifier.getClass().getName()
                        + ": " + new Trial (classifier, training).getAccuracy());

  System.out.println ("Accuracy on testing set:");
  double testAcc = new Trial (classifier, testing).getAccuracy();
  System.out.println (classifier.getClass().getName()
                        + ": " + testAcc);

  return testAcc;
}
 
开发者ID:kostagiolasn,项目名称:NucleosomePatternClassifier,代码行数:33,代码来源:TestPagedInstanceList.java


示例3: testNewFeatures

import cc.mallet.pipe.iterator.RandomTokenSequenceIterator; //导入依赖的package包/类
public void testNewFeatures ()
{
  ClassifierTrainer[] trainers = new ClassifierTrainer[1];
  trainers[0] = new MaxEntTrainer();

  Alphabet fd = dictOfSize (3);
  String[] classNames = new String[] {"class0", "class1", "class2"};

  Randoms r = new Randoms(1);
  InstanceList training = new InstanceList (r, fd, classNames, 50);
  expandDict (fd, 25);

  Classifier[] classifiers = new Classifier[trainers.length];
  for (int i = 0; i < trainers.length; i++)
    classifiers[i] = trainers[i].train (training);

  System.out.println ("Accuracy on training set:");
  for (int i = 0; i < trainers.length; i++)
    System.out.println (classifiers[i].getClass().getName()
                        + ": " + new Trial (classifiers[i], training).getAccuracy());

  InstanceList testing = new InstanceList (training.getPipe ());
  Iterator<Instance> iter = new RandomTokenSequenceIterator (
    r,  new Dirichlet (fd, 2.0),
    30, 0,
    10, 50,
    classNames);
  testing.addThruPipe (iter);

  for (int i = 0; i < testing.size (); i++) {
    Instance inst = testing.get (i);
    System.out.println ("DATA:"+inst.getData());
  }

  System.out.println ("Accuracy on testing set:");
  for (int i = 0; i < trainers.length; i++)
    System.out.println (classifiers[i].getClass().getName()
                        + ": " + new Trial (classifiers[i], testing).getAccuracy());
}
 
开发者ID:kostagiolasn,项目名称:NucleosomePatternClassifier,代码行数:40,代码来源:TestClassifiers.java


示例4: testRandomTrainedOn

import cc.mallet.pipe.iterator.RandomTokenSequenceIterator; //导入依赖的package包/类
private double testRandomTrainedOn (InstanceList training)
{
  ClassifierTrainer trainer = new MaxEntTrainer();

  Alphabet fd = dictOfSize (3);
  String[] classNames = new String[] {"class0", "class1", "class2"};

  Randoms r = new Randoms (1);
  Iterator<Instance> iter = new RandomTokenSequenceIterator (r,  new Dirichlet(fd, 2.0),
        30, 0, 10, 200, classNames);
  training.addThruPipe (iter);

  InstanceList testing = new InstanceList (training.getPipe ());
  testing.addThruPipe (new RandomTokenSequenceIterator (r,  new Dirichlet(fd, 2.0),
        30, 0, 10, 200, classNames));

  System.out.println ("Training set size = "+training.size());
  System.out.println ("Testing set size = "+testing.size());

  Classifier classifier = trainer.train (training);

  System.out.println ("Accuracy on training set:");
  System.out.println (classifier.getClass().getName()
                        + ": " + new Trial(classifier, training).getAccuracy());

  System.out.println ("Accuracy on testing set:");
  double testAcc = new Trial (classifier, testing).getAccuracy();
  System.out.println (classifier.getClass().getName()
                        + ": " + testAcc);

  return testAcc;
}
 
开发者ID:mimno,项目名称:Mallet,代码行数:33,代码来源:TestPagedInstanceList.java



注:本文中的cc.mallet.pipe.iterator.RandomTokenSequenceIterator类示例整理自Github/MSDocs等源码及文档管理平台,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。


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