本文整理汇总了Java中cc.mallet.types.InstanceList.CrossValidationIterator方法的典型用法代码示例。如果您正苦于以下问题：Java InstanceList.CrossValidationIterator方法的具体用法？Java InstanceList.CrossValidationIterator怎么用？Java InstanceList.CrossValidationIterator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.InstanceList的用法示例。
在下文中一共展示了InstanceList.CrossValidationIterator方法的1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: doTraining
import cc.mallet.types.InstanceList; //导入方法依赖的package包/类
private void doTraining(InstanceList trainList)
{
// train a classifier on the entire training set
logger.info("Training token classifier on entire data set (size=" + trainList.size() + ")...");
m_tokenClassifier = m_trainer.train(trainList);
Trial t = new Trial(m_tokenClassifier, trainList);
logger.info("Training set accuracy = " + t.getAccuracy());
if (m_numCV == 0)
return;
// train classifiers using cross validation
InstanceList.CrossValidationIterator cvIter = trainList.new CrossValidationIterator(m_numCV, m_randSeed);
int f = 1;
while (cvIter.hasNext()) {
f++;
InstanceList[] fold = cvIter.nextSplit();
logger.info("Training token classifier on cv fold " + f + " / " + m_numCV + " (size=" + fold[0].size() + ")...");
Classifier foldClassifier = m_trainer.train(fold[0]);
Trial t1 = new Trial(foldClassifier, fold[0]);
Trial t2 = new Trial(foldClassifier, fold[1]);
logger.info("Within-fold accuracy = " + t1.getAccuracy());
logger.info("Out-of-fold accuracy = " + t2.getAccuracy());
/*for (int x = 0; x < t2.size(); x++) {
logger.info("xxx pred:" + t2.getClassification(x).getLabeling().getBestLabel() + " true:" + t2.getClassification(x).getInstance().getLabeling());
}*/
for (int i = 0; i < fold[1].size(); i++) {
Instance inst = fold[1].get(i);
m_table.put(inst.getName(), foldClassifier);
}
}
}