weka.core.Instances.relationName()方法的使用及代码示例

x33g5p2x  于2022-01-21 转载在 其他  
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本文整理了Java中weka.core.Instances.relationName()方法的一些代码示例，展示了Instances.relationName()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。Instances.relationName()方法的具体详情如下：
包路径：weka.core.Instances
类名称：Instances
方法名：relationName

Instances.relationName介绍

[英]Returns the relation's name.
[中]返回关系的名称。

代码示例

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

/**
 * generates the XML structure for the header
 */
protected void headerToXML() {
 Element root;
 Element node;
 Element child;
 int i;
 root = m_Document.getDocumentElement();
 root.setAttribute(ATT_NAME, validContent(m_Instances.relationName()));
 root.setAttribute(ATT_VERSION, Version.VERSION);
 // create "header" node
 node = m_Document.createElement(TAG_HEADER);
 root.appendChild(node);
 // add all attributes
 child = m_Document.createElement(TAG_ATTRIBUTES);
 node.appendChild(child);
 for (i = 0; i < m_Instances.numAttributes(); i++) {
  addAttribute(child, m_Instances.attribute(i));
 }
}

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

/**
 * Samoa instances information.
 *
 * @param instances the instances
 * @return the instances
 */
public Instances samoaInstancesInformation(weka.core.Instances instances) {
  Instances samoaInstances;
  List<Attribute> attInfo = new ArrayList<Attribute>();
  for (int i = 0; i < instances.numAttributes(); i++) {
    attInfo.add(samoaAttribute(i, instances.attribute(i)));
  }
  samoaInstances = new Instances(instances.relationName(), attInfo, 0);
  samoaInstances.setClassIndex(instances.classIndex());
  return samoaInstances;
}

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

/**
 * Tells the panel to use a new set of instances.
 * 
 * @param inst a set of Instances
 */
public void setInstances(Instances inst) {
 m_Instances = inst;
 m_RelationNameLab.setText(m_Instances.relationName());
 m_RelationNameLab.setToolTipText(m_Instances.relationName());
 m_NumInstancesLab
   .setText(""
     + ((m_showZeroInstancesAsUnknown && m_Instances.numInstances() == 0) ? "?"
       : "" + m_Instances.numInstances()));
 m_NumAttributesLab.setText("" + m_Instances.numAttributes());
 m_sumOfWeightsLab
   .setText(""
     + ((m_showZeroInstancesAsUnknown && m_Instances.numInstances() == 0) ? "?"
       : "" + Utils.doubleToString(m_Instances.sumOfWeights(), 3)));
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * Sets up the structure for the plot instances.
 */
@Override
protected void determineFormat() {
 int numClusters;
 ArrayList<Attribute> hv;
 Attribute predictedCluster;
 ArrayList<String> clustVals;
 int i;
 numClusters = m_Evaluation.getNumClusters();
 hv = new ArrayList<Attribute>();
 clustVals = new ArrayList<String>();
 for (i = 0; i < numClusters; i++) {
  clustVals.add("cluster" + /* (i+1) */i);
 }
 predictedCluster = new Attribute("Cluster", clustVals);
 for (i = 0; i < m_Instances.numAttributes(); i++) {
  hv.add((Attribute) m_Instances.attribute(i).copy());
 }
 hv.add(predictedCluster);
 m_PlotInstances = new Instances(m_Instances.relationName() + "_clustered",
  hv, m_Instances.numInstances());
}

代码示例来源：origin: de.tudarmstadt.ukp.dkpro.tc/de.tudarmstadt.ukp.dkpro.tc.weka-gpl

/**
   * Applies a filter to reduce the dimension of attributes and reorders them to be used within
   * Meka
   * 
   * @param trainData
   * @param removeFilter
   * @return a dataset to be used with Meka
   * @throws Exception
   */
  public static Instances applyAttributeSelectionFilter(Instances trainData, Remove removeFilter)
    throws Exception
  {
    Instances filtered = Filter.useFilter(trainData, removeFilter);
    filtered.setClassIndex(trainData.classIndex());
    // swap attributes to fit MEKA
    MekaClassAttributes attFilter = new MekaClassAttributes();
    attFilter.setAttributeIndices(filtered.numAttributes() - trainData.classIndex() + 1
        + "-last");
    attFilter.setInputFormat(filtered);
    filtered = Filter.useFilter(filtered, attFilter);
    int newClassindex = filtered.classIndex();
    filtered.setRelationName(filtered.relationName().replaceAll("\\-C\\s[\\d]+",
        "-C " + newClassindex));

    return filtered;
  }
}

代码示例来源：origin: Waikato/meka

@Override
  public void run() {
    MultiLabelClassifier classifier;
    Result result;
    startBusy("Cross-validating...");
    try {
      classifier = (MultiLabelClassifier) m_GenericObjectEditor.getValue();
      log(OptionUtils.toCommandLine(classifier));
      log("Dataset: " + data.relationName());
      log("Class-index: " + data.classIndex());
      result = Evaluation.cvModel(classifier, data, m_Folds, m_TOP, m_VOP);
      addResultToHistory(
          result,
          new Object[]{classifier, new Instances(data, 0)},
          classifier.getClass().getName().replace("meka.classifiers.", "")
      );
      finishBusy();
    }
    catch (Exception e) {
      handleException("Evaluation failed:", e);
      finishBusy("Evaluation failed: " + e);
      JOptionPane.showMessageDialog(
          ClassifyTab.this,
          "Evaluation failed (CV):\n" + e,
          "Error",
          JOptionPane.ERROR_MESSAGE);
    }
  }
};

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

private Instances makeDataSetProbabilities(Instances insts, Instances format,
 weka.classifiers.Classifier classifier, String relationNameModifier)
 throws Exception {
 // adjust structure for InputMappedClassifier (if necessary)
 if (classifier instanceof weka.classifiers.misc.InputMappedClassifier) {
  format =
   ((weka.classifiers.misc.InputMappedClassifier) classifier)
    .getModelHeader(new Instances(format, 0));
 }
 String classifierName = classifier.getClass().getName();
 classifierName =
  classifierName.substring(classifierName.lastIndexOf('.') + 1,
   classifierName.length());
 Instances newInstances = new Instances(insts);
 for (int i = 0; i < format.classAttribute().numValues(); i++) {
  weka.filters.unsupervised.attribute.Add addF =
   new weka.filters.unsupervised.attribute.Add();
  addF.setAttributeIndex("last");
  addF.setAttributeName(classifierName + "_prob_"
   + format.classAttribute().value(i));
  addF.setInputFormat(newInstances);
  newInstances = weka.filters.Filter.useFilter(newInstances, addF);
 }
 newInstances.setRelationName(insts.relationName() + relationNameModifier);
 return newInstances;
}

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

/**
 * Adds an instance number attribute to the plottable instances,
 */
public void addInstanceNumberAttribute() {
 String originalRelationName = m_plotInstances.relationName();
 int originalClassIndex = m_plotInstances.classIndex();
 try {
  Add addF = new Add();
  addF.setAttributeName("Instance_number");
  addF.setAttributeIndex("first");
  addF.setInputFormat(m_plotInstances);
  m_plotInstances = Filter.useFilter(m_plotInstances, addF);
  m_plotInstances.setClassIndex(originalClassIndex + 1);
  for (int i = 0; i < m_plotInstances.numInstances(); i++) {
   m_plotInstances.instance(i).setValue(0, i);
  }
  m_plotInstances.setRelationName(originalRelationName);
 } catch (Exception ex) {
  ex.printStackTrace();
 }
}

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

/**
 * Gets the index of the instance with the closest threshold value to the
 * desired target
 * 
 * @param tcurve a set of instances that have been generated by this class
 * @param threshold the target threshold
 * @return the index of the instance that has threshold closest to the target,
 *         or -1 if this could not be found (i.e. no data, or bad threshold
 *         target)
 */
public static int getThresholdInstance(Instances tcurve, double threshold) {
 if (!RELATION_NAME.equals(tcurve.relationName())
  || (tcurve.numInstances() == 0) || (threshold < 0) || (threshold > 1.0)) {
  return -1;
 }
 if (tcurve.numInstances() == 1) {
  return 0;
 }
 double[] tvals = tcurve.attributeToDoubleArray(tcurve.numAttributes() - 1);
 int[] sorted = Utils.sort(tvals);
 return binarySearch(sorted, tvals, threshold);
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * Calculates the area under the precision-recall curve (AUPRC).
 * 
 * @param tcurve a previously extracted threshold curve Instances.
 * @return the PRC area, or Double.NaN if you don't pass in a ThresholdCurve
 *         generated Instances.
 */
public static double getPRCArea(Instances tcurve) {
 final int n = tcurve.numInstances();
 if (!RELATION_NAME.equals(tcurve.relationName()) || (n == 0)) {
  return Double.NaN;
 }
 final int pInd = tcurve.attribute(PRECISION_NAME).index();
 final int rInd = tcurve.attribute(RECALL_NAME).index();
 final double[] pVals = tcurve.attributeToDoubleArray(pInd);
 final double[] rVals = tcurve.attributeToDoubleArray(rInd);
 double area = 0;
 double xlast = rVals[n - 1];
 // start from the first real p/r pair (not the artificial zero point)
 for (int i = n - 2; i >= 0; i--) {
  double recallDelta = rVals[i] - xlast;
  area += (pVals[i] * recallDelta);
  xlast = rVals[i];
 }
 if (area == 0) {
  return Utils.missingValue();
 }
 return area;
}

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

/**
 * Gets the current settings of the C45Saver object.
 * 
 * @return an array of strings suitable for passing to setOptions
 */
@Override
public String[] getOptions() {
 Vector<String> options = new Vector<String>();
 if (retrieveFile() != null) {
  options.add("-o");
  options.add("" + retrieveFile());
 } else {
  options.add("-o");
  options.add("");
 }
 if (getInstances() != null) {
  options.add("-i");
  options.add("" + getInstances().relationName());
  options.add("-c");
  options.add("" + getInstances().classIndex());
 } else {
  options.add("-i");
  options.add("");
  options.add("-c");
  options.add("");
 }
 Collections.addAll(options, super.getOptions());
 return options.toArray(new String[0]);
}

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

/**
 * Sets up the structure for the plot instances.
 */
@Override
protected void determineFormat() {
 int numClusters;
 ArrayList<Attribute> hv;
 Attribute predictedCluster;
 ArrayList<String> clustVals;
 int i;
 numClusters = m_Evaluation.getNumClusters();
 hv = new ArrayList<Attribute>();
 clustVals = new ArrayList<String>();
 for (i = 0; i < numClusters; i++) {
  clustVals.add("cluster" + /* (i+1) */i);
 }
 predictedCluster = new Attribute("Cluster", clustVals);
 for (i = 0; i < m_Instances.numAttributes(); i++) {
  hv.add((Attribute) m_Instances.attribute(i).copy());
 }
 hv.add(predictedCluster);
 m_PlotInstances = new Instances(m_Instances.relationName() + "_clustered",
  hv, m_Instances.numInstances());
}

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

/**
 * displays some properties of the instances
 */
public void showProperties() {
 ArffPanel panel;
 ListSelectorDialog dialog;
 Vector<String> props;
 Instances inst;
 panel = getCurrentPanel();
 if (panel == null) {
  return;
 }
 inst = panel.getInstances();
 if (inst == null) {
  return;
 }
 if (inst.classIndex() < 0) {
  inst.setClassIndex(inst.numAttributes() - 1);
 }
 // get some data
 props = new Vector<String>();
 props.add("Filename: " + panel.getFilename());
 props.add("Relation name: " + inst.relationName());
 props.add("# of instances: " + inst.numInstances());
 props.add("# of attributes: " + inst.numAttributes());
 props.add("Class attribute: " + inst.classAttribute().name());
 props.add("# of class labels: " + inst.numClasses());
 dialog = new ListSelectorDialog(getParentFrame(), new JList(props));
 dialog.showDialog();
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * generates the XML structure for the header
 */
protected void headerToXML() {
 Element root;
 Element node;
 Element child;
 int i;
 root = m_Document.getDocumentElement();
 root.setAttribute(ATT_NAME, validContent(m_Instances.relationName()));
 root.setAttribute(ATT_VERSION, Version.VERSION);
 // create "header" node
 node = m_Document.createElement(TAG_HEADER);
 root.appendChild(node);
 // add all attributes
 child = m_Document.createElement(TAG_ATTRIBUTES);
 node.appendChild(child);
 for (i = 0; i < m_Instances.numAttributes(); i++) {
  addAttribute(child, m_Instances.attribute(i));
 }
}

代码示例来源：origin: Waikato/meka

@Override
  public void run() {
    MultiLabelClassifier classifier;
    Result result;
    startBusy("Incremental...");
    try {
      classifier = (MultiLabelClassifier) m_GenericObjectEditor.getValue();
      log(OptionUtils.toCommandLine(classifier));
      log("Dataset: " + data.relationName());
      log("Class-index: " + data.classIndex());
      result = IncrementalEvaluation.evaluateModelBatchWindow(classifier, data, m_Samples, 1., m_TOP, m_VOP);
      addResultToHistory(
          result,
          new Object[]{classifier, new Instances(data, 0)},
          classifier.getClass().getName().replace("meka.classifiers.", "")
      );
      finishBusy();
    }
    catch (Exception e) {
      handleException("Evaluation failed (incremental splits):", e);
      finishBusy("Evaluation failed: " + e);
      JOptionPane.showMessageDialog(
          ClassifyTab.this,
          "Evaluation failed:\n" + e,
          "Error",
          JOptionPane.ERROR_MESSAGE);
    }
  }
};

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

append("<html>\n");
append("<head>\n");
append("<title>Predictions for dataset " + sanitize(m_Header.relationName()) + "</title>\n");
append("</head>\n");
append("<body>\n");
append("<div align=\"center\">\n");
append("<h3>Predictions for dataset " + sanitize(m_Header.relationName()) + "</h3>\n");
append("<table border=\"1\">\n");
append("<tr>\n");
 append("<td>");
 boolean first = true;
 for (int i = 0; i < m_Header.numAttributes(); i++) {
  if (i == m_Header.classIndex())
   continue;
   if (!first)
    append("</td><td>");
   append(sanitize(m_Header.attribute(i).name()));
   first = false;

代码示例来源：origin: Waikato/weka-trunk

/**
 * Tells the panel to use a new set of instances.
 * 
 * @param inst a set of Instances
 */
public void setInstances(Instances inst) {
 m_Instances = inst;
 m_RelationNameLab.setText(m_Instances.relationName());
 m_RelationNameLab.setToolTipText(m_Instances.relationName());
 m_NumInstancesLab
   .setText(""
     + ((m_showZeroInstancesAsUnknown && m_Instances.numInstances() == 0) ? "?"
       : "" + m_Instances.numInstances()));
 m_NumAttributesLab.setText("" + m_Instances.numAttributes());
 m_sumOfWeightsLab
   .setText(""
     + ((m_showZeroInstancesAsUnknown && m_Instances.numInstances() == 0) ? "?"
       : "" + Utils.doubleToString(m_Instances.sumOfWeights(), 3)));
}

代码示例来源：origin: Waikato/weka-trunk

private Instances makeDataSetProbabilities(Instances insts, Instances format,
 weka.classifiers.Classifier classifier, String relationNameModifier)
 throws Exception {
 // adjust structure for InputMappedClassifier (if necessary)
 if (classifier instanceof weka.classifiers.misc.InputMappedClassifier) {
  format =
   ((weka.classifiers.misc.InputMappedClassifier) classifier)
    .getModelHeader(new Instances(format, 0));
 }
 String classifierName = classifier.getClass().getName();
 classifierName =
  classifierName.substring(classifierName.lastIndexOf('.') + 1,
   classifierName.length());
 Instances newInstances = new Instances(insts);
 for (int i = 0; i < format.classAttribute().numValues(); i++) {
  weka.filters.unsupervised.attribute.Add addF =
   new weka.filters.unsupervised.attribute.Add();
  addF.setAttributeIndex("last");
  addF.setAttributeName(classifierName + "_prob_"
   + format.classAttribute().value(i));
  addF.setInputFormat(newInstances);
  newInstances = weka.filters.Filter.useFilter(newInstances, addF);
 }
 newInstances.setRelationName(insts.relationName() + relationNameModifier);
 return newInstances;
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * Adds an instance number attribute to the plottable instances,
 */
public void addInstanceNumberAttribute() {
 String originalRelationName = m_plotInstances.relationName();
 int originalClassIndex = m_plotInstances.classIndex();
 try {
  Add addF = new Add();
  addF.setAttributeName("Instance_number");
  addF.setAttributeIndex("first");
  addF.setInputFormat(m_plotInstances);
  m_plotInstances = Filter.useFilter(m_plotInstances, addF);
  m_plotInstances.setClassIndex(originalClassIndex + 1);
  for (int i = 0; i < m_plotInstances.numInstances(); i++) {
   m_plotInstances.instance(i).setValue(0, i);
  }
  m_plotInstances.setRelationName(originalRelationName);
 } catch (Exception ex) {
  ex.printStackTrace();
 }
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * Gets the index of the instance with the closest threshold value to the
 * desired target
 * 
 * @param tcurve a set of instances that have been generated by this class
 * @param threshold the target threshold
 * @return the index of the instance that has threshold closest to the target,
 *         or -1 if this could not be found (i.e. no data, or bad threshold
 *         target)
 */
public static int getThresholdInstance(Instances tcurve, double threshold) {
 if (!RELATION_NAME.equals(tcurve.relationName())
  || (tcurve.numInstances() == 0) || (threshold < 0) || (threshold > 1.0)) {
  return -1;
 }
 if (tcurve.numInstances() == 1) {
  return 0;
 }
 double[] tvals = tcurve.attributeToDoubleArray(tcurve.numAttributes() - 1);
 int[] sorted = Utils.sort(tvals);
 return binarySearch(sorted, tvals, threshold);
}

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