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  3. weka.core.WekaEnumeration

Java 类weka.core.WekaEnumeration 实例源码

项目：repo.kmeanspp.silhouette_score    文件：Apriori.java    
/**
 * Method that finds all class association rules.
 * 
 * @throws Exception if an attribute is numeric
 */
private void findCarRulesQuickly() throws Exception {

  ArrayList<Object>[] rules;

  // Build rules
  for (int j = 0; j < m_Ls.size(); j++) {
    ArrayList<Object> currentLabeledItemSets = m_Ls.get(j);
    Enumeration<Object> enumLabeledItemSets = new WekaEnumeration<Object>(
      currentLabeledItemSets);
    while (enumLabeledItemSets.hasMoreElements()) {
      LabeledItemSet currentLabeledItemSet = (LabeledItemSet) enumLabeledItemSets
        .nextElement();
      rules = currentLabeledItemSet.generateRules(m_minMetric, false);
      for (int k = 0; k < rules[0].size(); k++) {
        m_allTheRules[0].add(rules[0].get(k));
        m_allTheRules[1].add(rules[1].get(k));
        m_allTheRules[2].add(rules[2].get(k));
      }
    }
  }
}
项目：repo.kmeanspp.silhouette_score    文件：KnowledgeFlowApp.java    
public TreeNode getChildAt(int index, boolean filterIsActive) {
  if (!filterIsActive) {
    return super.getChildAt(index);
  }
  if (children == null) {
    throw new ArrayIndexOutOfBoundsException("node has no children");
  }

  int realIndex = -1;
  int visibleIndex = -1;
  @SuppressWarnings("unchecked")
  Enumeration<InvisibleNode> e = new WekaEnumeration<InvisibleNode>(
    children);
  while (e.hasMoreElements()) {
    InvisibleNode node = e.nextElement();
    if (node.isVisible()) {
      visibleIndex++;
    }
    realIndex++;
    if (visibleIndex == index) {
      return (TreeNode) children.elementAt(realIndex);
    }
  }

  throw new ArrayIndexOutOfBoundsException("index unmatched");
}
项目：repo.kmeanspp.silhouette_score    文件：KnowledgeFlowApp.java    
public int getChildCount(boolean filterIsActive) {
  if (!filterIsActive) {
    return super.getChildCount();
  }
  if (children == null) {
    return 0;
  }

  int count = 0;
  @SuppressWarnings("unchecked")
  Enumeration<InvisibleNode> e = new WekaEnumeration<InvisibleNode>(
    children);
  while (e.hasMoreElements()) {
    InvisibleNode node = e.nextElement();
    if (node.isVisible()) {
      count++;
    }
  }

  return count;
}
项目：repo.kmeanspp.silhouette_score    文件：RDG1.java    
/**
 * Tries to classify an example.
 * 
 * @param example the example to classify
 * @return true if it could be classified
 * @throws Exception if something goes wrong
 */
private boolean classifyExample(Instance example) throws Exception {
  double classValue = -1.0;

  for (Enumeration<RuleList> e = new WekaEnumeration<RuleList>(m_DecisionList); e
    .hasMoreElements() && classValue < 0.0;) {
    RuleList rl = e.nextElement();
    classValue = rl.classifyInstance(example);
  }
  if (classValue >= 0.0) {
    example.setClassValue(classValue);
    return true;
  } else {
    return false;
  }
}
项目：umple    文件：Apriori.java    
/**
 * Method that finds all class association rules.
 * 
 * @throws Exception if an attribute is numeric
 */
private void findCarRulesQuickly() throws Exception {

  ArrayList<Object>[] rules;

  // Build rules
  for (int j = 0; j < m_Ls.size(); j++) {
    ArrayList<Object> currentLabeledItemSets = m_Ls.get(j);
    Enumeration<Object> enumLabeledItemSets = new WekaEnumeration<Object>(
      currentLabeledItemSets);
    while (enumLabeledItemSets.hasMoreElements()) {
      LabeledItemSet currentLabeledItemSet = (LabeledItemSet) enumLabeledItemSets
        .nextElement();
      rules = currentLabeledItemSet.generateRules(m_minMetric, false);
      for (int k = 0; k < rules[0].size(); k++) {
        m_allTheRules[0].add(rules[0].get(k));
        m_allTheRules[1].add(rules[1].get(k));
        m_allTheRules[2].add(rules[2].get(k));
      }
    }
  }
}
项目：umple    文件：KnowledgeFlowApp.java    
public TreeNode getChildAt(int index, boolean filterIsActive) {
  if (!filterIsActive) {
    return super.getChildAt(index);
  }
  if (children == null) {
    throw new ArrayIndexOutOfBoundsException("node has no children");
  }

  int realIndex = -1;
  int visibleIndex = -1;
  @SuppressWarnings("unchecked")
  Enumeration<InvisibleNode> e = new WekaEnumeration<InvisibleNode>(
    children);
  while (e.hasMoreElements()) {
    InvisibleNode node = e.nextElement();
    if (node.isVisible()) {
      visibleIndex++;
    }
    realIndex++;
    if (visibleIndex == index) {
      return (TreeNode) children.elementAt(realIndex);
    }
  }

  throw new ArrayIndexOutOfBoundsException("index unmatched");
}
项目：umple    文件：KnowledgeFlowApp.java    
public int getChildCount(boolean filterIsActive) {
  if (!filterIsActive) {
    return super.getChildCount();
  }
  if (children == null) {
    return 0;
  }

  int count = 0;
  @SuppressWarnings("unchecked")
  Enumeration<InvisibleNode> e = new WekaEnumeration<InvisibleNode>(
    children);
  while (e.hasMoreElements()) {
    InvisibleNode node = e.nextElement();
    if (node.isVisible()) {
      count++;
    }
  }

  return count;
}
项目：umple    文件：RDG1.java    
/**
 * Tries to classify an example.
 * 
 * @param example the example to classify
 * @return true if it could be classified
 * @throws Exception if something goes wrong
 */
private boolean classifyExample(Instance example) throws Exception {
  double classValue = -1.0;

  for (Enumeration<RuleList> e = new WekaEnumeration<RuleList>(m_DecisionList); e
    .hasMoreElements() && classValue < 0.0;) {
    RuleList rl = e.nextElement();
    classValue = rl.classifyInstance(example);
  }
  if (classValue >= 0.0) {
    example.setClassValue(classValue);
    return true;
  } else {
    return false;
  }
}
项目：repo.kmeanspp.silhouette_score    文件：LabeledItemSet.java    
/**
 * Updates counter of a specific item set
 * 
 * @param itemSets an item sets
 * @param instancesNoClass instances without the class attribute
 * @param instancesClass the values of the class attribute sorted according to
 *          instances
 */
public static void upDateCounters(ArrayList<Object> itemSets,
  Instances instancesNoClass, Instances instancesClass) {

  for (int i = 0; i < instancesNoClass.numInstances(); i++) {
    Enumeration<Object> enu = new WekaEnumeration<Object>(itemSets);
    while (enu.hasMoreElements()) {
      ((LabeledItemSet) enu.nextElement()).upDateCounter(
        instancesNoClass.instance(i), instancesClass.instance(i));
    }
  }

}
项目：repo.kmeanspp.silhouette_score    文件：LabeledItemSet.java    
/**
 * Updates counter of a specific item set
 * 
 * @param itemSets an item sets
 * @param instancesNoClass instances without the class attribute
 * @param instancesClass the values of the class attribute sorted according to
 *          instances
 */
public static void upDateCountersTreatZeroAsMissing(
  ArrayList<LabeledItemSet> itemSets, Instances instancesNoClass,
  Instances instancesClass) {
  for (int i = 0; i < instancesNoClass.numInstances(); i++) {
    Enumeration<LabeledItemSet> enu = new WekaEnumeration<LabeledItemSet>(
      itemSets);
    while (enu.hasMoreElements()) {
      enu.nextElement().upDateCounterTreatZeroAsMissing(
        instancesNoClass.instance(i), instancesClass.instance(i));
    }
  }
}
项目：repo.kmeanspp.silhouette_score    文件：Apriori.java    
/**
 * Method that finds all association rules and performs significance test.
 * 
 * @throws Exception if an attribute is numeric
 */
private void findRulesBruteForce() throws Exception {

  ArrayList<Object>[] rules;

  // Build rules
  for (int j = 1; j < m_Ls.size(); j++) {
    ArrayList<Object> currentItemSets = m_Ls.get(j);
    Enumeration<Object> enumItemSets = new WekaEnumeration<Object>(
      currentItemSets);
    while (enumItemSets.hasMoreElements()) {
      AprioriItemSet currentItemSet = (AprioriItemSet) enumItemSets
        .nextElement();
      // AprioriItemSet currentItemSet = new
      // AprioriItemSet((ItemSet)enumItemSets.nextElement());
      rules = currentItemSet.generateRulesBruteForce(m_minMetric,
        m_metricType, m_hashtables, j + 1, m_instances.numInstances(),
        m_significanceLevel);
      for (int k = 0; k < rules[0].size(); k++) {
        m_allTheRules[0].add(rules[0].get(k));
        m_allTheRules[1].add(rules[1].get(k));
        m_allTheRules[2].add(rules[2].get(k));

        m_allTheRules[3].add(rules[3].get(k));
        m_allTheRules[4].add(rules[4].get(k));
        m_allTheRules[5].add(rules[5].get(k));
      }
    }
  }
}
项目：repo.kmeanspp.silhouette_score    文件：Apriori.java    
/**
 * Method that finds all association rules.
 * 
 * @throws Exception if an attribute is numeric
 */
private void findRulesQuickly() throws Exception {

  ArrayList<Object>[] rules;
  // Build rules
  for (int j = 1; j < m_Ls.size(); j++) {
    ArrayList<Object> currentItemSets = m_Ls.get(j);
    Enumeration<Object> enumItemSets = new WekaEnumeration<Object>(
      currentItemSets);
    while (enumItemSets.hasMoreElements()) {
      AprioriItemSet currentItemSet = (AprioriItemSet) enumItemSets
        .nextElement();
      // AprioriItemSet currentItemSet = new
      // AprioriItemSet((ItemSet)enumItemSets.nextElement());
      rules = currentItemSet.generateRules(m_minMetric, m_hashtables, j + 1);
      for (int k = 0; k < rules[0].size(); k++) {
        m_allTheRules[0].add(rules[0].get(k));
        m_allTheRules[1].add(rules[1].get(k));
        m_allTheRules[2].add(rules[2].get(k));

        if (rules.length > 3) {
          m_allTheRules[3].add(rules[3].get(k));
          m_allTheRules[4].add(rules[4].get(k));
          m_allTheRules[5].add(rules[5].get(k));
        }
      }
    }
  }
}
项目：repo.kmeanspp.silhouette_score    文件：ItemSet.java    
/**
 * Updates counters for a set of item sets and a set of instances.
 * 
 * @param itemSets the set of item sets which are to be updated
 * @param instances the instances to be used for updating the counters
 */
public static void upDateCounters(ArrayList<Object> itemSets,
  Instances instances) {

  for (int i = 0; i < instances.numInstances(); i++) {
    Enumeration<Object> enu = new WekaEnumeration<Object>(itemSets);
    while (enu.hasMoreElements()) {
      ((ItemSet) enu.nextElement()).upDateCounter(instances.instance(i));
    }
  }
}
项目：repo.kmeanspp.silhouette_score    文件：ItemSet.java    
/**
 * Updates counters for a set of item sets and a set of instances.
 * 
 * @param itemSets the set of item sets which are to be updated
 * @param instances the instances to be used for updating the counters
 */
public static void upDateCountersTreatZeroAsMissing(
  ArrayList<Object> itemSets, Instances instances) {
  for (int i = 0; i < instances.numInstances(); i++) {
    Enumeration<Object> enu = new WekaEnumeration<Object>(itemSets);
    while (enu.hasMoreElements()) {
      ((ItemSet) enu.nextElement()).updateCounterTreatZeroAsMissing(instances
        .instance(i));
    }
  }
}
项目：repo.kmeanspp.silhouette_score    文件：BIRCHCluster.java    
/**
 * Generate all examples of the dataset.
 * 
 * @param random the random number generator to use
 * @param format the dataset format
 * @return the instance generated
 * @throws Exception if format not defined
 */
public Instances generateExamples(Random random, Instances format)
  throws Exception {
  Instance example = null;

  if (format == null) {
    throw new Exception("Dataset format not defined.");
  }

  // generate examples for one cluster after another
  int cNum = 0;
  for (Enumeration<Cluster> enm = new WekaEnumeration<Cluster>(m_ClusterList); enm
    .hasMoreElements(); cNum++) {
    Cluster cl = enm.nextElement();
    double stdDev = cl.getStdDev();
    int instNum = cl.getInstNum();
    double[] center = cl.getCenter();
    String cName = "c" + cNum;

    for (int i = 0; i < instNum; i++) {
      // generate example
      example = generateInstance(format, random, stdDev, center, cName);

      if (example != null) {
        example.setDataset(format);
      }
      format.add(example);
    }
  }

  return (format);
}
项目：repo.kmeanspp.silhouette_score    文件：BIRCHCluster.java    
/**
 * Compiles documentation about the data generation before the generation
 * process
 * 
 * @return string with additional information
 */
@Override
public String generateStart() {
  StringBuffer docu = new StringBuffer();

  int sumInst = 0;
  int cNum = 0;
  for (Enumeration<Cluster> enm = new WekaEnumeration<Cluster>(m_ClusterList); enm
    .hasMoreElements(); cNum++) {
    Cluster cl = enm.nextElement();
    docu.append("%\n");
    docu.append("% Cluster: c" + cNum + "\n");
    docu.append("% ----------------------------------------------\n");
    docu.append("% StandardDeviation: "
      + Utils.doubleToString(cl.getStdDev(), 2) + "\n");
    docu.append("% Number of instances: " + cl.getInstNum() + "\n");
    sumInst += cl.getInstNum();
    double[] center = cl.getCenter();
    docu.append("% ");
    for (int i = 0; i < center.length - 1; i++) {
      docu.append(Utils.doubleToString(center[i], 2) + ", ");
    }
    docu.append(Utils.doubleToString(center[center.length - 1], 2) + "\n");
  }
  docu.append("%\n% ----------------------------------------------\n");
  docu.append("% Total number of instances: " + sumInst + "\n");
  docu.append("%                            in " + cNum + " clusters\n");
  docu.append("% Pattern chosen           : ");
  if (m_Pattern == GRID) {
    docu.append("GRID, " + "distance multiplier = "
      + Utils.doubleToString(m_DistMult, 2) + "\n");
  } else if (m_Pattern == SINE) {
    docu.append("SINE\n");
  } else {
    docu.append("RANDOM\n");
  }

  return docu.toString();
}
项目：repo.kmeanspp.silhouette_score    文件：RDG1.java    
/**
 * classifies the given example
 * 
 * @param example the instance to classify
 * @return the classification
 * @throws Exception if classification fails
 */
private double classifyInstance(Instance example) throws Exception {
  boolean passedAllTests = true;
  for (Enumeration<Test> e = new WekaEnumeration<Test>(m_RuleList); passedAllTests
    && e.hasMoreElements();) {
    Test test = e.nextElement();
    passedAllTests = test.passesTest(example);
  }
  if (passedAllTests) {
    return m_ClassValue;
  } else {
    return -1.0;
  }
}
项目：repo.kmeanspp.silhouette_score    文件：RDG1.java    
/**
 * Classify example with maximum vote the following way. With every rule in
 * the decisionlist, it is evaluated if the given instance could be the class
 * of the rule. Finally the class value that receives the highest number of
 * votes is assigned to the example.
 * 
 * @param example example to be reclassified
 * @return instance with new class value
 * @throws Exception if classification fails
 */
private Instance votedReclassifyExample(Instance example) throws Exception {
  int classVotes[] = new int[getNumClasses()];
  for (int i = 0; i < classVotes.length; i++) {
    classVotes[i] = 0;
  }

  for (Enumeration<RuleList> e = new WekaEnumeration<RuleList>(m_DecisionList); e
    .hasMoreElements();) {
    RuleList rl = e.nextElement();
    int classValue = (int) rl.classifyInstance(example);
    if (classValue >= 0) {
      classVotes[classValue]++;
    }
  }
  int maxVote = 0;
  int vote = -1;
  for (int i = 0; i < classVotes.length; i++) {
    if (classVotes[i] > maxVote) {
      maxVote = classVotes[i];
      vote = i;
    }
  }
  if (vote >= 0) {
    example.setClassValue(vote);
  } else {
    throw new Exception("Error in instance classification.");
  }

  return example;
}
项目：umple    文件：LabeledItemSet.java    
/**
 * Updates counter of a specific item set
 * 
 * @param itemSets an item sets
 * @param instancesNoClass instances without the class attribute
 * @param instancesClass the values of the class attribute sorted according to
 *          instances
 */
public static void upDateCounters(ArrayList<Object> itemSets,
  Instances instancesNoClass, Instances instancesClass) {

  for (int i = 0; i < instancesNoClass.numInstances(); i++) {
    Enumeration<Object> enu = new WekaEnumeration<Object>(itemSets);
    while (enu.hasMoreElements()) {
      ((LabeledItemSet) enu.nextElement()).upDateCounter(
        instancesNoClass.instance(i), instancesClass.instance(i));
    }
  }

}
项目：umple    文件：LabeledItemSet.java    
/**
 * Updates counter of a specific item set
 * 
 * @param itemSets an item sets
 * @param instancesNoClass instances without the class attribute
 * @param instancesClass the values of the class attribute sorted according to
 *          instances
 */
public static void upDateCountersTreatZeroAsMissing(
  ArrayList<LabeledItemSet> itemSets, Instances instancesNoClass,
  Instances instancesClass) {
  for (int i = 0; i < instancesNoClass.numInstances(); i++) {
    Enumeration<LabeledItemSet> enu = new WekaEnumeration<LabeledItemSet>(
      itemSets);
    while (enu.hasMoreElements()) {
      enu.nextElement().upDateCounterTreatZeroAsMissing(
        instancesNoClass.instance(i), instancesClass.instance(i));
    }
  }
}
项目：umple    文件：Apriori.java    
/**
 * Method that finds all association rules and performs significance test.
 * 
 * @throws Exception if an attribute is numeric
 */
private void findRulesBruteForce() throws Exception {

  ArrayList<Object>[] rules;

  // Build rules
  for (int j = 1; j < m_Ls.size(); j++) {
    ArrayList<Object> currentItemSets = m_Ls.get(j);
    Enumeration<Object> enumItemSets = new WekaEnumeration<Object>(
      currentItemSets);
    while (enumItemSets.hasMoreElements()) {
      AprioriItemSet currentItemSet = (AprioriItemSet) enumItemSets
        .nextElement();
      // AprioriItemSet currentItemSet = new
      // AprioriItemSet((ItemSet)enumItemSets.nextElement());
      rules = currentItemSet.generateRulesBruteForce(m_minMetric,
        m_metricType, m_hashtables, j + 1, m_instances.numInstances(),
        m_significanceLevel);
      for (int k = 0; k < rules[0].size(); k++) {
        m_allTheRules[0].add(rules[0].get(k));
        m_allTheRules[1].add(rules[1].get(k));
        m_allTheRules[2].add(rules[2].get(k));

        m_allTheRules[3].add(rules[3].get(k));
        m_allTheRules[4].add(rules[4].get(k));
        m_allTheRules[5].add(rules[5].get(k));
      }
    }
  }
}
项目：umple    文件：Apriori.java    
/**
 * Method that finds all association rules.
 * 
 * @throws Exception if an attribute is numeric
 */
private void findRulesQuickly() throws Exception {

  ArrayList<Object>[] rules;
  // Build rules
  for (int j = 1; j < m_Ls.size(); j++) {
    ArrayList<Object> currentItemSets = m_Ls.get(j);
    Enumeration<Object> enumItemSets = new WekaEnumeration<Object>(
      currentItemSets);
    while (enumItemSets.hasMoreElements()) {
      AprioriItemSet currentItemSet = (AprioriItemSet) enumItemSets
        .nextElement();
      // AprioriItemSet currentItemSet = new
      // AprioriItemSet((ItemSet)enumItemSets.nextElement());
      rules = currentItemSet.generateRules(m_minMetric, m_hashtables, j + 1);
      for (int k = 0; k < rules[0].size(); k++) {
        m_allTheRules[0].add(rules[0].get(k));
        m_allTheRules[1].add(rules[1].get(k));
        m_allTheRules[2].add(rules[2].get(k));

        if (rules.length > 3) {
          m_allTheRules[3].add(rules[3].get(k));
          m_allTheRules[4].add(rules[4].get(k));
          m_allTheRules[5].add(rules[5].get(k));
        }
      }
    }
  }
}
项目：umple    文件：ItemSet.java    
/**
 * Updates counters for a set of item sets and a set of instances.
 * 
 * @param itemSets the set of item sets which are to be updated
 * @param instances the instances to be used for updating the counters
 */
public static void upDateCounters(ArrayList<Object> itemSets,
  Instances instances) {

  for (int i = 0; i < instances.numInstances(); i++) {
    Enumeration<Object> enu = new WekaEnumeration<Object>(itemSets);
    while (enu.hasMoreElements()) {
      ((ItemSet) enu.nextElement()).upDateCounter(instances.instance(i));
    }
  }
}
项目：umple    文件：ItemSet.java    
/**
 * Updates counters for a set of item sets and a set of instances.
 * 
 * @param itemSets the set of item sets which are to be updated
 * @param instances the instances to be used for updating the counters
 */
public static void upDateCountersTreatZeroAsMissing(
  ArrayList<Object> itemSets, Instances instances) {
  for (int i = 0; i < instances.numInstances(); i++) {
    Enumeration<Object> enu = new WekaEnumeration<Object>(itemSets);
    while (enu.hasMoreElements()) {
      ((ItemSet) enu.nextElement()).updateCounterTreatZeroAsMissing(instances
        .instance(i));
    }
  }
}
项目：umple    文件：BIRCHCluster.java    
/**
 * Generate all examples of the dataset.
 * 
 * @param random the random number generator to use
 * @param format the dataset format
 * @return the instance generated
 * @throws Exception if format not defined
 */
public Instances generateExamples(Random random, Instances format)
  throws Exception {
  Instance example = null;

  if (format == null) {
    throw new Exception("Dataset format not defined.");
  }

  // generate examples for one cluster after another
  int cNum = 0;
  for (Enumeration<Cluster> enm = new WekaEnumeration<Cluster>(m_ClusterList); enm
    .hasMoreElements(); cNum++) {
    Cluster cl = enm.nextElement();
    double stdDev = cl.getStdDev();
    int instNum = cl.getInstNum();
    double[] center = cl.getCenter();
    String cName = "c" + cNum;

    for (int i = 0; i < instNum; i++) {
      // generate example
      example = generateInstance(format, random, stdDev, center, cName);

      if (example != null) {
        example.setDataset(format);
      }
      format.add(example);
    }
  }

  return (format);
}
项目：umple    文件：BIRCHCluster.java    
/**
 * Compiles documentation about the data generation before the generation
 * process
 * 
 * @return string with additional information
 */
@Override
public String generateStart() {
  StringBuffer docu = new StringBuffer();

  int sumInst = 0;
  int cNum = 0;
  for (Enumeration<Cluster> enm = new WekaEnumeration<Cluster>(m_ClusterList); enm
    .hasMoreElements(); cNum++) {
    Cluster cl = enm.nextElement();
    docu.append("%\n");
    docu.append("% Cluster: c" + cNum + "\n");
    docu.append("% ----------------------------------------------\n");
    docu.append("% StandardDeviation: "
      + Utils.doubleToString(cl.getStdDev(), 2) + "\n");
    docu.append("% Number of instances: " + cl.getInstNum() + "\n");
    sumInst += cl.getInstNum();
    double[] center = cl.getCenter();
    docu.append("% ");
    for (int i = 0; i < center.length - 1; i++) {
      docu.append(Utils.doubleToString(center[i], 2) + ", ");
    }
    docu.append(Utils.doubleToString(center[center.length - 1], 2) + "\n");
  }
  docu.append("%\n% ----------------------------------------------\n");
  docu.append("% Total number of instances: " + sumInst + "\n");
  docu.append("%                            in " + cNum + " clusters\n");
  docu.append("% Pattern chosen           : ");
  if (m_Pattern == GRID) {
    docu.append("GRID, " + "distance multiplier = "
      + Utils.doubleToString(m_DistMult, 2) + "\n");
  } else if (m_Pattern == SINE) {
    docu.append("SINE\n");
  } else {
    docu.append("RANDOM\n");
  }

  return docu.toString();
}
项目：umple    文件：RDG1.java    
/**
 * classifies the given example
 * 
 * @param example the instance to classify
 * @return the classification
 * @throws Exception if classification fails
 */
private double classifyInstance(Instance example) throws Exception {
  boolean passedAllTests = true;
  for (Enumeration<Test> e = new WekaEnumeration<Test>(m_RuleList); passedAllTests
    && e.hasMoreElements();) {
    Test test = e.nextElement();
    passedAllTests = test.passesTest(example);
  }
  if (passedAllTests) {
    return m_ClassValue;
  } else {
    return -1.0;
  }
}
项目：umple    文件：RDG1.java    
/**
 * Classify example with maximum vote the following way. With every rule in
 * the decisionlist, it is evaluated if the given instance could be the class
 * of the rule. Finally the class value that receives the highest number of
 * votes is assigned to the example.
 * 
 * @param example example to be reclassified
 * @return instance with new class value
 * @throws Exception if classification fails
 */
private Instance votedReclassifyExample(Instance example) throws Exception {
  int classVotes[] = new int[getNumClasses()];
  for (int i = 0; i < classVotes.length; i++) {
    classVotes[i] = 0;
  }

  for (Enumeration<RuleList> e = new WekaEnumeration<RuleList>(m_DecisionList); e
    .hasMoreElements();) {
    RuleList rl = e.nextElement();
    int classValue = (int) rl.classifyInstance(example);
    if (classValue >= 0) {
      classVotes[classValue]++;
    }
  }
  int maxVote = 0;
  int vote = -1;
  for (int i = 0; i < classVotes.length; i++) {
    if (classVotes[i] > maxVote) {
      maxVote = classVotes[i];
      vote = i;
    }
  }
  if (vote >= 0) {
    example.setClassValue(vote);
  } else {
    throw new Exception("Error in instance classification.");
  }

  return example;
}