示例#1
0
  /**
   * Set cutpoints for a single attribute using MDL.
   *
   * @param index the index of the attribute to set cutpoints for
   * @param data the data to work with
   */
  protected void calculateCutPointsByMDL(int index, Instances data) {

    // Sort instances
    data.sort(data.attribute(index));

    // Find first instances that's missing
    int firstMissing = data.numInstances();
    for (int i = 0; i < data.numInstances(); i++) {
      if (data.instance(i).isMissing(index)) {
        firstMissing = i;
        break;
      }
    }
    m_CutPoints[index] = cutPointsForSubset(data, index, 0, firstMissing);
  }
示例#2
0
  /**
   * Creates a C4.5-type split on the given data.
   *
   * @exception Exception if something goes wrong
   */
  public void buildClassifier(Instances trainInstances) throws Exception {

    // Initialize the remaining instance variables.
    m_numSubsets = 0;
    m_splitPoint = Double.MAX_VALUE;
    m_infoGain = 0;
    m_gainRatio = 0;

    // Different treatment for enumerated and numeric
    // attributes.
    if (trainInstances.attribute(m_attIndex).isNominal()) {
      handleEnumeratedAttribute(trainInstances);
    } else {
      trainInstances.sort(trainInstances.attribute(m_attIndex));
      handleNumericAttribute(trainInstances);
    }
  }