本文整理了Java中weka.core.Utils.roundDouble()方法的一些代码示例，展示了Utils.roundDouble()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。Utils.roundDouble()方法的具体详情如下：
包路径：weka.core.Utils
类名称：Utils
方法名：roundDouble

Utils.roundDouble介绍

[英]Rounds a double to the given number of decimal places.
[中]将双精度四舍五入到给定的小数位数。

代码示例

代码示例来源：origin: nz.ac.waikato.cms.weka/multiInstanceLearning

} else if (m_NumIterations == 1) {
 text.append("No boosting possible, one classifier used: Weight = "
  + Utils.roundDouble(m_Beta[0], 2) + "\n");
 text.append("Base classifiers:\n" + m_Models[0].toString());
} else {
 for (int i = 0; i < m_NumIterations; i++) {
  text.append("\n\n" + i + ": Weight = "
   + Utils.roundDouble(m_Beta[i], 2) + "\nBase classifier:\n"
   + m_Models[i].toString());

代码示例来源：origin: Waikato/weka-trunk

for (int i = 0; i < m_NumIterationsPerformed; i++) {
 text.append(m_Classifiers[i].toString() + "\n\n");
 text.append("Weight: " + Utils.roundDouble(m_Betas[i], 2) + "\n\n");

代码示例来源：origin: nz.ac.waikato.cms.weka/weka-stable

for (int i = 0; i < m_NumIterationsPerformed; i++) {
 text.append(m_Classifiers[i].toString() + "\n\n");
 text.append("Weight: " + Utils.roundDouble(m_Betas[i], 2) + "\n\n");

代码示例来源：origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Prints label for subset index of instances (eg class).
 *
 * @exception Exception if something goes wrong
 */
public final String dumpLabel(int index,Instances data) throws Exception {
 StringBuffer text;
 text = new StringBuffer();
 text.append(((Instances)data).classAttribute().
   value(m_distribution.maxClass(index)));
 text.append(" ("+Utils.roundDouble(m_distribution.perBag(index),2));
 if (Utils.gr(m_distribution.numIncorrect(index),0))
  text.append("/"+Utils.roundDouble(m_distribution.numIncorrect(index),2));
 text.append(")");
 return text.toString();
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * Prints label for subset index of instances (eg class).
 *
 * @exception Exception if something goes wrong
 */
public final String dumpLabel(int index,Instances data) throws Exception {
 StringBuffer text;
 text = new StringBuffer();
 text.append(((Instances)data).classAttribute().
   value(m_distribution.maxClass(index)));
 text.append(" ("+Utils.roundDouble(m_distribution.perBag(index),2));
 if (Utils.gr(m_distribution.numIncorrect(index),0))
  text.append("/"+Utils.roundDouble(m_distribution.numIncorrect(index),2));
 text.append(")");
 return text.toString();
}

代码示例来源：origin: nz.ac.waikato.cms.weka/weka-stable

System.out.println("5.5 rounded: " + Utils.round(5.5));
System.out.println("5.55555 rounded to 2 decimal places: "
 + Utils.roundDouble(5.55555, 2));

代码示例来源：origin: Waikato/weka-trunk

System.out.println("5.5 rounded: " + Utils.round(5.5));
System.out.println("5.55555 rounded to 2 decimal places: "
 + Utils.roundDouble(5.55555, 2));

代码示例来源：origin: nz.ac.waikato.cms.weka/meka

/**
 * CVModel - Split D into train/test folds, and then train and evaluate on each one.
 * @param    h         a multi-dim. classifier
 * @param    D           data
 * @param    numFolds test data
 * @param    top         Threshold OPtion (pertains to multi-label data only)
 * @return    an array of 'numFolds' Results
 */
public static Result[] cvModel(MultilabelClassifier h, Instances D, int numFolds, String top) throws Exception {
  Result r[] = new Result[numFolds];
  for(int i = 0; i < numFolds; i++) {
    Instances D_train = D.trainCV(numFolds,i);
    Instances D_test = D.testCV(numFolds,i);
    if (h.getDebug()) System.out.println(":- Fold ["+i+"/"+numFolds+"] -: "+MLUtils.getDatasetName(D)+"\tL="+D.classIndex()+"\tD(t:T)=("+D_train.numInstances()+":"+D_test.numInstances()+")\tLC(t:T)="+Utils.roundDouble(MLUtils.labelCardinality(D_train,D.classIndex()),2)+":"+Utils.roundDouble(MLUtils.labelCardinality(D_test,D.classIndex()),2)+")");
    r[i] = evaluateModel(h, D_train, D_test, top);
  }
  return r;
}

代码示例来源：origin: net.sf.meka/meka

Instances D_train = D.trainCV(numFolds,i);
Instances D_test = D.testCV(numFolds,i);
if (h.getDebug()) System.out.println(":- Fold ["+i+"/"+numFolds+"] -: "+MLUtils.getDatasetName(D)+"\tL="+D.classIndex()+"\tD(t:T)=("+D_train.numInstances()+":"+D_test.numInstances()+")\tLC(t:T)="+Utils.roundDouble(MLUtils.labelCardinality(D_train,D.classIndex()),2)+":"+Utils.roundDouble(MLUtils.labelCardinality(D_test,D.classIndex()),2)+")");

代码示例来源：origin: Waikato/meka

Instances D_train = D.trainCV(numFolds,i);
Instances D_test = D.testCV(numFolds,i);
if (h.getDebug()) System.out.println(":- Fold ["+i+"/"+numFolds+"] -: "+MLUtils.getDatasetName(D)+"\tL="+D.classIndex()+"\tD(t:T)=("+D_train.numInstances()+":"+D_test.numInstances()+")\tLC(t:T)="+Utils.roundDouble(MLUtils.labelCardinality(D_train,D.classIndex()),2)+":"+Utils.roundDouble(MLUtils.labelCardinality(D_test,D.classIndex()),2)+")");

代码示例来源：origin: nz.ac.waikato.cms.weka/meka

if (h.getDebug()) System.out.println(":- Dataset -: "+MLUtils.getDatasetName(allInstances)+"\tL="+allInstances.classIndex()+"\tD(t:T)=("+train.numInstances()+":"+test.numInstances()+")\tLC(t:T)="+Utils.roundDouble(MLUtils.labelCardinality(train,allInstances.classIndex()),2)+":"+Utils.roundDouble(MLUtils.labelCardinality(test,allInstances.classIndex()),2)+")");

代码示例来源：origin: net.sf.meka/meka

if (h.getDebug()) System.out.println(":- Dataset -: "+MLUtils.getDatasetName(D_train)+"\tL="+L+"\tD(t:T)=("+D_train.numInstances()+":"+D_test.numInstances()+")\tLC(t:T)="+Utils.roundDouble(MLUtils.labelCardinality(D_train,L),2)+":"+Utils.roundDouble(MLUtils.labelCardinality(D_test,L),2)+")");

代码示例来源：origin: Waikato/meka

if (h.getDebug()) System.out.println(":- Dataset -: "+MLUtils.getDatasetName(D_train)+"\tL="+L+"\tD(t:T)=("+D_train.numInstances()+":"+D_test.numInstances()+")\tLC(t:T)="+Utils.roundDouble(MLUtils.labelCardinality(D_train,L),2)+":"+Utils.roundDouble(MLUtils.labelCardinality(D_test,L),2)+")");